Cleveland Chapter of the ASA
Past Meetings
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- 2007 Talks
- Wednesday, December 12, 2007
- Building Risk-Adjustment Models for the Assessment of Obstetrical Quality
:
Jennifer L. Bailit and Thomas E. Love
-
In this talk we will discuss the data and statistical challenges involved in creating risk-adjustment
models for the evaluation of obstetrical care.
Many traditional measures of obstetrical quality, such as raw hospital cesarean rates,
are becoming obsolete. When cesarean rates are compared without risk adjustment for
maternal risk factors, hospitals treating complex patients appear to be providing poor
quality care when in fact they may be providing superb care. Additionally, hospitals
providing care to low risk patients may appear to be providing high quality care when in fact they are not.
The statistical and other methodological considerations related to producing valuable
risk-adjustment measures in this context are substantial, especially in light of the many
additional issues related to working in a "hot button" field like the assessment of obstetrical care. We will share some
of our more interesting experiences from the varied perspectives of a clinical researcher and a biostatistician.
- Friday, March 30, 2007
- Adventures in Teaching with Technology
:
Webster West
-
There are a tremendous number of technology resources
available for teaching statistics. These range from
interactive web-based applets to video lectures. The
trick is often times determining which resources
actually work and how best to incorporate them into
your courses. Techniques for evaluating technology
learning tools and some common integration approaches
will be discussed. A discussion of the potential
impact of technology on the future of statistics
education will also be provided.
- 2006 Talks
- Wednesday, November 1, 2006
- Missing Data Methodology in Malaria Studies
:
Rhoderick Machekano
-
Efficacy studies of malaria treatments can be plagued by indeterminate outcomes for some patients.
The study motivating this work defines the outcome of interest (treatment failure) as recrudescence and for
some subjects, it is unclear whether a recurrence of malaria is due to that or new infection.
This results in a specific kind of missing data. The effect of missing data in causal inference
problems is widely recognized. Methods that adjust for possible bias from missing data include a
variety of imputation procedures (extreme case analysis, hot-deck, single and multiple imputation),
inverse weighting methods, and likelihood based methods (data augmentation, EM procedures and their extensions).
In this talk, I focus on multiple imputation, two inverse weighting procedures
(the inverse probability weighted (IPW) and the doubly robust (DR) estimators),
and a likelihood based methodology (Gcomputation), comparing the methods' applicability to the efficient
estimation of malaria treatments effects.
I present results from simulation studies as well as results from an application to
malaria efficacy studies from Uganda.
- Wednesday, September 20, 2006
- What Mathematics and Forrest Gump Teach Us About Lotteries
:
Ron Wasserstein
-
Since the inception of the Kansas Lottery in 1987, I have been speaking to school and civic groups
about the lottery--how it works, what the probability of winning is and how that is computed, and most importantly,
what the probability is of coming out ahead (a winner!) in the lottery.
Initial efforts involved a standard lecture, but before long it became clear that more was needed.
Thus, I have developed a computer game that simulates playing the lottery multiple times.
Playing the game is not only fun, but it also shows students vividly what happens in the long run.
Accompanying the computer game is a set of PowerPoint slides which teach about the lottery and probability.
In this presentation to the Cleveland Chapter, I will "teach" this subject, demonstrating how these tools can
be used as outreach to local groups. I will also provide the computer game and slides on CD for free use by chapter members.
- Wednesday, April 12, 2006
- Bayesian and Frequentist Methods for Provider Profiling Using Risk-Adjusted Assessments of Medical Outcomes
:
Joe Sedransk
-
We propose a new method and compare conventional and Bayesian methodologies that are used or proposed
for use for 'provider profiling,' an evaluation of the quality of health care. The conventional approaches
to computing these provider assessments are to use likelihood-based frequentist methodologies, and the
new Bayesian method is patterned after these. For each of three models we compare the frequentist and
Bayesian approaches using the data employed by the New York State Department of Health for its
annually released reports that profile hospitals permitted to perform coronary artery bypass graft surgery.
Additional, constructed, data sets are used to sharpen our conclusions. With the advances of Markov Chain
Monte Carlo methods, Bayesian methods are easily implemented and are preferable to standard frequentist
methods for models with a binary dependent variable since the latter always rely on asymptotic approximations.
Comparisons across methods associated with different models are important because of current proposals
to use random effect (exchangeable) models for provider profiling. We also summarize and discuss important
issues in the conduct of provider profiling such as inclusion of provider characteristics in the model and
choice of criteria for determining unsatisfactory performance.
- 2005 Talks
- December 15, 2005
- Hands-on Bayesian Data Analysis using WinBUGS [doubled as fall workshop]
:
William F. Guthrie, National Institute of Standards and Technology
-
This workshop is designed to provide statisticians, scientists, or engineers
with the tools necessary to begin to use Bayesian inference in applied problems. Participants in the course
will learn the basics of Bayesian modeling and inference using Markov chain Monte Carlo simulation with the
open-source software package WinBUGS.
The workshop will introduce some of the theory underlying Bayesian analysis,
but will primarily focus on Bayesian analysis of "real-world" scientific applications using examples from
collaborative research with NIST scientists and engineers. Topics discussed will include Bayesian modeling,
Markov chain Monte Carlo algorithms, convergence tests, model validation, and inference.
- September 14, 2005
- SAT scores for sale? Assessment of Commercial Test
Preparation Via Optimal Full Matching.
:
Ben B. Hansen, University of Michigan
-
Post-stratification is an old, flexible, efficient, and
conceptually plain statistical technique. If a treatment and a
control group are to be compared, and if every treated
subject is sufficiently similar to one or more controls as to
justify comparison to it, then with the right stratification one
can rightly estimate treatment effects simply by averaging and
differencing outcomes.
An impediment is that post-stratification is practically feasible,
usually, only when there are few covariates. Often there
are many covariates, not just one or two, on which
subjects should be similar so as to justify their comparison.
For the purpose of estimating treatment effects, this issue is
dispensed with by propensity scores, which reduce the dimension
of the covariates to one. Because of this, observational studies
are increasingly analyzed by way of stratification along a
propensity score. Commonly used methods for stratifying along an
estimated propensity include pair matching, matching with
multiple controls, and subclassification along quintiles of the
score.
Now the "right" stratification --- one that pairs only subjects
with sufficiently similar values of the estimated score --- need
not take a simple form, in which case the commonly used methods
of stratification carry no guarantee of finding it. However,
there is always a so-called full matching that is at least as
good as any other stratification. This will be illustrated with
a case study of full matching, with propensity scores, applied to
estimate effects of commercial coaching for the SAT. I have
created an add-on package to R to perform optimal full matching,
"optmatch," and I shall also illustrate its use.
- June 1, 2005
- When Statistical Process Control Outweighs Randomized Clinical Trials
:
Dr. Mireya Diaz-Insua, Case Western Reserve University
Clinical trials are the pinnacle in the hierarchy of evidence-based
medicine. The main reason being the control they exert over observable
and non-observable bias by virtue of the randomization process. We find
proof of the use of trials as far back as verses
in the book of Daniel
in the Old Testament. In the late 1920s, Amberson designed the first
randomized trial in medicine (known to us) to assess the efficacy of
sanocrysin in the treatment of tuberculosis, 43 years after Peirce
incorporated randomization in experimentation. Despite its established
validity in the chain of evidence, there are circumstances when a
randomized trial is not feasible because of time constraints and/or ethical
concerns. In these situations, viable alternatives are necessary.
Vaccine or treatment for diminishing the effect of outbreaks, parachute
jumping, lethal conditions that require approaches with fast results
are just examples of such scenarios. We show here tools from Statistical
Process Control (SPC) that present a feasible alternative for those
cases. We show the implementation of such strategy within the context of
a specific case study of vaccine development and testing for rabies
conducted by Pasteur in the 1880s, when randomization in experimentation
was almost unknown. SPC tools will prove through this example how and
when they are a plausible alternative to the paradigmatic randomized
clinical trial. This is joint work with Dr. Duncan Neuhauser, and
together they have produced three recent articles on related topics for
the journal Quality and Safety in Health Care.
- 2004 Talks
- December 1, 2004
- Calls for 911 Service: A Collaboration Between CSU and the Cleveland City Police
:
Dr. John P. Holcomb, Jr., Cleveland State University
-
In the last two years, professors from the Cleveland State University
Department of Mathematics and Sociology have been working closely with
the City of Cleveland Police Department. This partnership has resulted
in access to police records cataloging all 911 calls for the city
since 1995. In the presentation, I will share summary graphs and statistics
as it relates to calls for service throughout the city and by various
districts. I will also share various models that undergraduate and graduate
students have developed to predict the number of calls for service.
- September 1, 2004
- Regression Modeling of Left and Right-Censored Outcomes
:
Jeff Hammel, Cleveland Clinic
-
This presentation is motivated by the study of the susceptibility of
bacteria to antimicrobial drugs. Susceptibility (or its opposite,
resistance) is often measured by the minimum drug concentration required
to kill the bacteria, or simply the minimum inhibitory concentration (MIC).
An MIC can be measured for a bacteria sample from a patient diagnosed
with an infection. The MIC is often determined in a laboratory using a
finite set of titred drug concentrations. When the MIC is below the
lowest tested concentration or above the largest tested concentration,
then the recorded value is left- or right-censored, respectively. That
is, it is of the form '≤ k1' or '>k2'. The tested concentrations are
also typically integer powers of 2 mg/L, in which case the censored
values can be written as '≤2L' or '>2R' for integer values of L and R.
MIC data of this form is easily analyzed using either SAS or S-plus.
I will demonstrate code for doing these analyses.
- June 2, 2004
- An Introduction to the R Language
:
Ethan Katz, Cleveland Clinic
Jason Connor, Carnegie Mellon University
- A basic, interactive, hands-on introduction to the R
language, including statistical analysis and graphics procedures. Topics include:
Getting started with R: downloading R, obtaining documentation, and
using the help system.
Statistics with R: descriptive statistics, statistical tests, and
model fitting.
Graphics with R: basics and examples
- February 27, 2004
- Analytical Tools in the SAS System
:
William Kuhfield, SAS Institute
Andrew Karp, Sierra Information Services, Inc.
- Dr. Kuhfield, (a Cleveland-area native) who is a leading developer
in the Research and Development group at SAS Worldwide Headquarters in Cary, NC.,
will present an introduction to the field of experimental design. His talk will
focus on an easy-to-use tool for building efficient experimental designs.
The second presentation is a tutorial on how to build and interpret predictive
models using PROC LOGISTIC. This analytic technique is frequently used in both
medical/scientific and business analytic projects to predict the probability
that an event (e.g., product purchase, disease outcome) will occur. This
tutorial will be given by Andrew Karp, a well-known SAS Software consultant,
trainer, and SAS user group meeting presenter.
- 2003 Talks
- December 3, 2003
- Propensity Scores: What Do They Do, How Should I Use Them, And Why Should I Care?
:
Thomas E. Love,
Case Western Reserve University and MetroHealth Medical Center
- Many statistical problems aim to draw causal inferences about the effects of
policies, treatments or interventions. But the data in most cases are
observational, rather than experimental - that is, the data are collected
through the observation of systems as they operate in normal practice,
rather than under carefully controlled conditions. In particular, the
investigators have no control over the assignments of exposures.
Such data are relatively inexpensive to obtain, and may represent the
"real world" more effectively than the results of randomized experiments.
However, in using an observational study to estimate a treatment effect,
the "exposed" and "control" groups often differ substantially in terms
of background characteristics.
This talk will provide a friendly introduction to propensity score methods
for reducing the impact of selection bias on observational studies.
- October 27, 2003 (Fall Workshop)
- Analysis of Curves: Esteban Walker, University of Tennessee
- Advances in technology have dramatically increased
the amount and quality of data that are recorded in all areas of human
endeavor. Thousands of measurements are available nowadays in situations
where previously only a few measurements, at given points in time or space,
were taken. These measurements allow the reconstruction of the whole profile
or "signature". Basically, the profile becomes the unit of analysis.
This seminar will discuss two problems with profiles: (1) how to determine
if predetermined sets of curves are different, and (2) how to identify clusters
in a set of curves. Examples from various fields will be presented.
Instructions on the implementation of these techniques in S-Plus and SAS will
be given.
- September 17, 2003
- Reversible Jump Markov Chain Monte Carlo For Linear Regression Models: Patrick Gaffney, Lubrizol
- Reversible Jump Markov Chain Monte Carlo (RJ-MCMC) is increasing in
popularity as witnessed by the number of citations to the seminal paper
by Green. This methodology gives the statistician a means of solving
difficult problems where a parametric model has been proposed but the
number of terms in the model is unknown. Some examples include change-point
analysis, image analysis, and gene discovery.
Several issues arise in practice: initialization of the chain,
the proposal mechanism for parameters, correct formation of the
acceptance ratio, and final model selection. In this talk, I will
address these issues when RJ-MCMC is applied to solve linear regression
models in a Bayesian framework. The lessons learned can readily be
applied to more complex situations.
- June 4, 2003
- An Introduction to Value-Added Methods for Teacher Accountability: J.R. Lockwood, RAND
Statistics Group
- As underscored by the federal No Child Left Behind Act of 2001,
a currently active and central education policy initiative is the
use of scores on standardized achievement tests to hold educators
accountable for student outcomes. One of the challenges to this
endeavor is combining test score information into a single measure
that provides evidence of school or teacher effectiveness.
Although many states and districts rely on simple aggregate
score averages or differences, a few are exploring more complex
models that leverage longitudinal data on students to isolate the
"value added" by a particular teacher or school. This modeling
approach has taken a number of forms and is generally referred to as
"value-added modeling" (VAM). Enthusiasm for this approach stems
from the belief that it can remove the effects of factors not under
the control of the school, such as prior performance and socioeconomic
status, and thereby provide a more accurate indicator of school or teacher
effectiveness.
In this talk, we critically evaluate this claim in the context of
models used to isolate teacher effects. We briefly review the principal
existing modeling approaches and conclusions from the literature. We then
present a general multivariate, longitudinal mixed-model that incorporates
the crossed grouping structures inherent to longitudinal student data linked
to teachers. We discuss the potential impact of model misspecifications,
including missing student covariates and assumptions about the accumulation
of teacher effects over time, on key inferences made from the models. We
conclude with an assessment of the strengths, limitations, and the most
challenging unresolved issues of value-added models as a tool for teacher
accountability.
- March 5, 2003
- The Biostatistician's Role in Health Economics: Adrienne Heerey, Cleveland
Clinic Foundation
- Rates of healthcare expenditure have risen in excess of inflation
in the past decade. The fruits of intensive research in the '80s
are becoming realized, resulting in a number of expensive medical
interventions becoming available. Simultaneously, focus is being
placed on reducing healthcare expenditure. As a result, the
requirement for economic evaluation has become vital in the effort
to obtain the best value from a given healthcare budget. Due to the
scarcity of health economists, many bio-statisticians are being
asked to contribute to these studies. This presentation details the
fundamental components of cost effectiveness evaluation and economic
modeling and highlights statistical queries faced in these studies.
- 2002 Talks
- December 4, 2002
- Financial and Estate Planning by the Estate Planning Team, Inc.: Stuart Kleiner,
Estate Planning Team, Inc.
-
Estate Planning is "the action an individual takes to
maximize use of their assets to enhance lifestyle and
support their desired level of activity, to protect
their estate from financial devastation in the event
of an unforeseen nursing home stay and to provide for
their loved ones through the transfer of property by
gifting during lifetime or through inheritance after
death, while minimizing all administrative costs
and taxes." Mr. Kleiner will discuss basic legal
documents every person should have, retirement planning,
reducing income and estate taxes, multigenerational
family financial planning, college funding, how to help
your parents with planning, common planning mistakes,
how to select and coordinate professional advisors, etc.
- November 6, 2002
- Industrial Applications in Statistics: Robert Mason, Southwest Research
Institute
- Statistics has been used to solve data problems in the United
States for over 160 years. The fields of application continue to expand and include
common areas such as the physical, engineering, and biological sciences as well as
more recent applications such as in space and environmental sciences. This presentation
provides an interesting application resulting from recent work conducted at Southwest
Research Institute. It concerns a statistical experiment conducted to determine if
honeybees can be used to detect land mines. The results have recently appeared in
major newspapers, magazines, and network news programs.
- October 14, 2002 (Fall Workshop)
- A Review: Missing Data: Joseph Schafer, Pennsylvania State
University
- Statistical procedures for missing data have vastly
improved in the last two decades, yet misconception and unsound practice
still abound. In this seminar, we will
- frame the missing-data problem from a statistician's viewpoint
- introduce fundamental concepts regarding the distribution of
missingness and missing at random (MAR)
- review older, ad hoc procedures including case deletion and
single imputation, discussing their merits and weaknesses
- discuss the theory, implementation and use of maximum likelihood
(ML) for incomplete data problems
- introduce the idea of multiple imputation (MI), discuss its
properties, and demonstrate its use on a real data example
- discuss some of the latest developments in the missing-data
literature that have appeared in the last five years, including
weighted estimating equations and methods for handling missing
values that are not MAR.
- September 4, 2002
- Optimal Price Rules, Administered Prices and Suboptimal
Prevention Evidence from a Medicare Program: Avi Dor, Case Western
Reserve University
- Pricing methodologies in Medicare vary from one
component of the system to another, often leading to conflicting
incentives. Failure to recognize linkages between them may result in
inefficient allocation of resources and higher overall costs. To
motivate the analysis, I derive pricing rules for a welfare-maximizing
regulator. I show that while optimal inpatient payments are standard
Ramsey prices, optimal outpatient payments must incorporate net loss due
to unnecessary hospitalizations, as well as supply elasticities. A
myopic regulator will tend to ignore this, leading to underprovision of
preventive services. The dialysis program represents a useful case for
empirical investigation, since payments for maintenance services more
rigidly determined than payments for related hospital care. Given
constant prices, empirical analysis focuses on the effect of dialysis
intensity on various measures of hospital use. Results indicate that
greater dialysis intensity reduces hospital use. Moreover, this is found
even at moderate or high levels of intensity, where dialysis is viewed
ex ante as being adequate. A simple cost-benefit calculation suggests
that for every dollar of additional spending on outpatient intensity,
about $1.5 in hospital expenditures can be saved. This suggest that the
current pricing structure within aspects of the Medicare program is
inefficient, and underscores the problem of regulatory myopia.
-
- June 5, 2002
- Assessing Risk and Fairness: The Role of Statistical Science in
Policy: David W. Scott, Rice University
- Probability theory provides a mathematical framework
for modeling risk. Philosophy considers fundamental questions of the
nature and meaning of chance. But it falls upon statistical science to
collect and analyze data to estimate risk, influence policy, and make
decisions. Insurance provides a compelling case study for notions of
fairness and subsidy. This talk will examine the notion of a fair game
and consider its application in areas including decision making, social
security, medical insurance, and exit polling. What are some of the
elements of "fair'' policies? A deeper understanding of statistical
modeling and evaluation would illuminate subsidies implicit in public
policy and would sharpen political debate.
-
- May 1, 2002
- Defining 1-Sided P-Values in a Genetic Problem: Robert C.
Elston, Case Western Reserve University
- Fisher defined the P-value as the probability of an
observed result or anything more extreme, i.e. anything that would alert
the research worker even more than the observed result to the
possibility that the null hypothesis is not true. Depending on the
situation, the appropriate P-value should be 1-sided or 2-sided. If
segregation at a genetic locus underlies the etiology of a disease, then
pairs of siblings who are both affected with the disease will tend to
share a larger number of alleles identical by descent at a linked marker
locus. Under the null hypothesis that the marker locus is not linked to
such a disease locus, the siblings will share 0, 1 or 2 marker alleles
identical by descent with probabilities ¼, ½ and ¼,
respectively. The definition of a 1-sided P-value in this situation will
be discussed.
- April 3, 2002
- The SAS Solution to Warranty Analysis: Jeff Wright, SAS
Institute
- SAS is in the process of bringing to market a
solution product for Warranty Analysis. This solution has been initially
developed for the automotive (and automotive supplier) industry but will
soon be applicable to any discrete manufacturer who must both manage
warranty claims/costs. The solution will integrate warranty data with
key customer, vehicle, production, and geographic information so that
the organization can achieve a level of process knowledge that
translates into significant value. The solution allows manufacturers to
automatically detect emerging quality issues before they make it to the
top of the 'issue list'; as needed, use statistical analysis to
determine root causes to quickly to focus resources in an accurate and
timely manner (using SAS Enterprise Guide, a graphical user interface to
the SAS system); as needed, use data mining techniques for further
inquiry into manufacturing and customer relationship issues (using SAS
Enterprise Miner); forecast warranty costs to protect against financial
risk. A demo of the Warranty Solution will be presented along with quick
looks at SAS Enterprise Guide and SAS Enterprise Miner.
- March 6, 2002
- Design of Computer Experiments to Optimize the Mean of a Response:
Bill Notz, The Ohio State University
- For purposes of this talk, a computer experiment is
assumed to consist of computer code that produces deterministic
responses for a given set of inputs. We consider the situation in which
there are two types of inputs; manufacturing variables and noise
variables. Manufacturing variables are those that can be controlled by
the product designer. Noise variables cannot be controlled but have
values that follow some probability distribution. We seek the values of
the manufacturing variables that optimize the mean of a response. The
approach is Bayesian; the prior information is that the response is a
draw from a stationary Gaussian stochastic process with correlation
function belonging to a parametric family with unknown parameters.
Following an initial design, a sequential strategy is used to select
values of the inputs at which to observe the response. This strategy
involves computing, for each unobserved set of values of the inputs, the
posterior expected "improvement" over the current best guess
at the optimum and the next set of inputs to observe are those that
maximize this expected improvement. The strategy is illustrated with
examples. Other issues regarding computer experiments will be addressed
as they arise.
- February 6, 2002
- Geometric Morphometric Techniques to Design Skull Prostheses:
David Dean, Case Western Reserve University
- Recently, we have begun to look at the use of
patient specific radiological data as the source for highly accurate
computer-aided-manufacture (CAM) of tissue engineered prosthetic
implants. The templates for the CAD (Computer-Aided Design) of these
prosthetics comes from shape study of human anatomy referred to as
geometric morphometrics. Traditional multivariate statistical
morphometrics (circa 1880-1980) indirectly gave rise to these methods
which are truly a graft from the engineering literature on best fit
(rigid body) and warping (forced fit through bending) algorithms.
Geometric morphometrics has only truly been a field of inquiry and
application for a decade, or so. There are no textbooks, but there are
several good conference and review texts as well as journal papers. Most
emphasize two primary algorithms, Procrustes and Thin Plate Spine, for
best fit and warping, respectively. The primary novelty in these methods
is that the transformed landmark coordinates themselves, instead of
linear, area, volume, or other traditional measurements, have become the
statistical basis of shape measurement. These approaches are useful in
describing phenomena of average biological shape or biological symmetry.
These data have significant implications for CAD/CAM of human
prosthetics.
It is expected to facilitate highly accurate control of
implant-host fit and complex internal structures that promote
resorption. This work has been done with a 3D Systems (Valencia, CA) SLA
250/40 stereolithographic device. Stereolithographic CAM of PPF
components begins with a computer-aided-design (CAD) STL (public
stereolithography ASCII data format) file generated in a 3D (i.e.,
solid) CAD interface. Now that more than 20 patients have received
implants produced in this fashion, we are beginning to look at more
efficient ways to use stereolithographic production of skull prostheses.
Previously other groups and we have used patient CT images as source
data to print a skull model of the patient. These large skull models are
expensive to produce. Additionally, the manual work that follows to
design and manufacture an implant is also expensive. We will present new
technology that allows us to print the implant directly thereby saving
the cost of printing the patient's skull and expense of several
generations of manual work.
- January 9, 2002 (Cleveland Chapter Presidential Address)
- Analyzing Over-dispersed Count Data from One-Way Designs:
Nancy Campbell, John Carroll University
- A comparative study of several possible statistical
tests for analyzing over-dispersed count data from completely randomized
one-way experimental designs will be discussed. Specifically a Monte
Carlo study was done in which tests involving the general linear model
on the raw data and on transformations of the data were compared to
tests based on the generalized linear model utilizing either the Poisson
or negative binomial distribution. The problem was motivated by a
co-author's frequent encountering of over-dispersed count data from such
experiments, often involving small means and small sample sizes. The
past simulation study will be explained and conclusions drawn, and a
current related comparative study will be discussed as well. In
addition, an ongoing undergraduate research project by Computer Science
majors at John Carroll done in conjunction with the current study will
be discussed.
- 2001 Talks
- December 5, 2001
- The Breast Implant Controversy: Statisticians and Epidemiologists
Meet the Media and the Legal Profession: W. Michael O'Fallon, Mayo
Clinic and Past-President ASA
- In 1992, the FDA announced a moratorium on the
installation of Breast Implants ending a 30 year period of increasing
utilization of this technology. Women with surgically removed or
deformed breasts and women who desired breast augmentation had access to
such implants in the U.S since about 1962 and were by-and-large
satisfied. However, some case reports of a variety of connective tissue
diseases occurring in women with implants and a small number of court
cases led the FDA to use its newly obtained regulatory authority to
request safety data from the various manufacturers of implant materials.
When such data were not forthcoming and/or were deemed incomplete or
unsatisfactory the moratorium was declared. A firestorm of lawsuits
ensued and pleas for scientific information on the topic were issued.
The Department of Health Sciences Research at the Mayo Clinic provided
the first response with a paper published in the New England Journal of
Medicine in 1994. This presentation discusses our contacts with the
media and primarily with the legal profession following this
publication. Some of our experiences were exhilarating but most were
nerve wracking, depressing, disillusioning, and even frightening.
However, we have survived.
- November 7, 2001
- Two-Stage Group Screening in the Presence of Noise Factors:
Angela Dean, The Ohio State University
- A major advantage of factorial experiments is the
information that they provide on interactions. When the number of
factors is large and little prior knowledge on the various factorial
effects is available, conventional fractional factorial experiments
capable of estimating interactions require too many observations to be
economically viable. To overcome this problem, interactions are
frequently dropped from consideration and assumed to be negligible,
often without substantive justification. In industrial experimentation,
in particular, the loss of information on interactions is a serious
problem, because a key tool for product improvement is the exploitation
of interactions between design (control) factors which can be set in the
product specification, and noise factors which cannot. Two different
strategies for ''group screening'' will be presented for a large number
of factors, over two stages of experimentation, with particular emphasis
on the detection of interactions between design and noise factors. Three
criteria are used to guide the choice of screening technique, and also
the size of the groups of factors for study in the first stage
experiment. The criteria seek to minimize the expected total number of
observations in the experiment, the probability that the experiment size
exceeds a pre-specified target, and the proportion of active factorial
effects which are not detected. Examples will be used to illustrate the
methodology, and some issues and open questions for the practical
implementation of the results will be discussed.
- October 3, 2001 (Fall Workshop)
- Experiments: Planning, Analysis, and Parameter Design
Optimization: C. F. Jeff Wu, The University of Michigan
- This seminar will be based on the book "Experiments:
Planning, Analysis, and Parameter Design Optimization" by Jeff Wu
and Mike Hamada (2000). Course notes will be made available to
attendees. This book contains many new methods not found in existing
textbooks, and covers more than 80 data sets and 200 exercises. The new
tools covered include robust parameter design, use of minimum aberration
criterion for optimal factor assignment, orthogonal arrays of economic
run size, analysis strategies to exploit interactions, experiments for
reliability improvement, and analysis of experiments with non-normal
responses. Data from real experiments will be used to illustrate
concepts. Time will be reserved for questions and discussion.
- September 5, 2001
- Irregular Factorial Designs: Tena I. Katsaounis, Mansfield
Restaurants Inc
- Partially Balanced arrays with N runs, m factors,
two symbols, strength t greater than two and a given index will be
discussed as being Partially Balanced arrays with N runs, m factors, two
symbols and of strength equal to two. Formulas for calculating the
corresponding index, given any number of factors m, will be presented.
This method is useful in showing easily non existence of a Partially
Balanced array with N runs, m factors, two symbols, strength t greater
than two and a given index. Construction of irregular factorial designs
using this method will be discussed. Such designs belong to the class of
Partially Balanced or PB1 or Extended PB1 arrays.
- June 6, 2001
- A Case Study: An Inside Job by an Outsider: Dennis Fox,
Cleveland Technical Societies Council President
- The presentation will focus on three things. The "Case"
study, the results, trends and hopes for these Fourth grade students at
a local elementary school. Thoughts on how to make meaningful changes in
classes is the second part of the presentation with comments on Time's
Schools of the Year Schools That Stretch article in the May 21, 2001
magazine. Finally, a report about a new charter school I hope will use
EQL, DDM, QL and SEAQL techniques and other technical societies
educational outreach programs as a basis of the curriculum that is
scheduled to open this fall in Cleveland. We will be very open to
discussion on where and how we go from here at Case Elementary and other
programs. Some of the answers, while not difficult or surprising (in
hindsight), may surprise you. We are all educators; some of us just
received formal training in it.
- May 2, 2001 (A Worskshop sponsored by the ASA Council of
Chapters)
- Permutation Tests: A Guide for Practicioners: Phillip Good,
Information Research
- This is a one-half day course on permutation
methods. It is intended for practicing statisticians and others with
interest in applying statistical methods. High school algebra is assumed
but no higher-level mathematics is required. Some familiarity with
computer simulation would also be helpful. Attendees will be given
historical background on resampling methods and a formal introduction to
these methods. Emphasis will be placed on the wide variety of
applications of the techniques, the computer-intensive nature of
implementation along with many examples and "real world"
applications. The course is intended for those who use statistical
methods in their work. This includes practitioners in medicine,
business, engineering and the social sciences. It also will be useful to
professors of statistics and those who do statistical research but may
not be familiar with resampling methods and want to be updated on the
latest advances in methodology and application. Dr. Good is the author
of two popular texts on resampling methods. Resampling is a powerful
technique which has only recently seen an explosion in applications due
to enhancements in computational techniques that make these
computer-intensive methods practical.
- April 4, 2001
- Design of Two-Level Fractional Factorials with Vague Prior
Information: Arthur G. Holms
- An experimenter's prior information, however vague,
is incorporated, according to the vagueness, into the design of
expansible sequences of two-level fractional factorials with crossed
classification block effects, and all simpler cases. The experimenter's
prior subjective probabilities of the importance of model coefficients,
block parameters, and likely stopping stages of expansible sequences are
used to maximize the expected utility of a design by making optimum
selections of model coefficients from the estimates aliased and
confounded sets of model coefficients, for all physical to plan variable
matchings, for the experiment designer's choices of groups and subgroups
of defining contrasts. Differing groups and subgroups can then be
compared under the condition of optimal coefficient selection and
physical to plan variable matching.
- March 7, 2001
- Statistics Education and the Making Statistics More Effective in
Schools of Business (MSMESB) Conferences: Thomas Love, Case Western
Reserve University
- The Making Statistics More Effective in Schools of
Business (MSMESB) conferences have been held annually since 1986. Since
its inception, MSMESB has focused on improving the teaching of
statistics and statistical thinking, on cross-disciplinary research, and
cross-pollination between academia and industry, and on continuous
improvement in business education. The conferences have led to
substantial changes in curricular content, modes of delivery, and
supplemental material in business (and other) programs all over the
world. This talk describes the impact of MSMESB on the teaching of
statistics, especially the development of textbooks and software. The
talk traces some of MSMESB's history and draws out some practical
recommendations. We also highlight some key challenges and opportunities
for the future. Earlier versions of this work were jointly prepared with
David Hildebrand, of the Wharton School. The MSMESB web site houses
details of many of the sessions at
http://weatherhead.cwru.edu/msmesb
- February 7, 2001
- African American Study of Kidney Disease and Hypertension -
Design and Update : Jennifer J. Gassman, The Cleveland Clinic
Foundation
- The African American Study of Kidney Disease and
Hypertension is a factorial design study of the effect of
antihypertensive regimen and level of blood pressure control on the
progression of kidney disease in African Americans with hypertensive
nephrosclerosis. In this presentation, the study design will be reviewed
and there will be an update on the progress of the study.
- January 3, 2001
- Uses and Abuses of Proficiency Tests: Robert S. Butler,
BFGoodrich
- In recent years tremendous emphasis has been placed
on the idea of quality in education. To this end many states, including
Ohio, have embraced the concept of proficiency testing as a means of
quality control. While the pronouncements from Columbus have all of the
verbal hallmarks of a quality control effort they have little else. This
is unfortunate because, with proper analysis, the proficiency data can
provide valuable information about many aspects of the education
process. In order to provide an understanding of what can and cannot be
expected from proficiency testing, the talk will focus on the analysis
of the 1996-1999 Shaker Heights 4th grade proficiency scores.
- 2000 Talks
- December 6, 2000 (Cleveland Chapter Presidential Address)
- Cryptography, Primes, and Privacy: Wm. O. Orgel, Solutions;
et cetera
- There are three words that describe privacy. They
are secrecy, secrecy, and secrecy. Article IV of the Bill of Rights
guarantees: "The right of the people to be secure in their persons,
houses, papers, and effects...". Modern technology is making the
privacy of medical records, banking, credit, and our bodies (Genetics),
etc. an international issue, which disturbs many people.
Cryptography-not thought of by most people very often-is supposed to be
at work protecting our privacy every second of every day. Why do we
trust cryptology to protect our privacy/security, both personal and
national? From whom are we being protected? We will discuss the
historical connection among ancient, modern and contemporary mathematics
(prime numbers) to the Internet, e.g., Euclid is usually discussed
respecting Geometry; and Fermat his Last Theorem, but not this time.
There are "keys" to making cryptography work, and we'll
discuss them. Is the future of cryptography in Quantum Computing?
Finally, we will discuss the Awards of "Privacy International".
- November 2, 2000
- Statistics for a New Century: Meeting the Needs of a World of
Data: Richard Scheaffer, University of Florida, President ASA
- The world is awash in data. Most people are aware of
the importance and power of data in their professional and personal
lives, and many attempt to use data in making everyday decisions. But
few are educated in ways that would allow them to comprehend more fully
the vast array of uses (and misuses) of data and to use more effectively
the quantitative information that confronts them daily. Even fewer are
aware of the fact that formal study of statistics can serve to
strengthen their own academic preparation for a wide variety of careers.
This talk will provide an overview of the current efforts in the United
States to infuse statistics into the school (K-12) curriculum and to
enhance opportunities for undergraduates to learn more about statistics.
Ties to similar efforts in the international community will be
mentioned. The goals are to empower students through improved
quantitative literacy and to provide strong foundations for careers that
depend increasingly on data. Among the strengths of these efforts are
the terrific interest they have generated among educators and students
at all levels; among the weaknesses are the tendency for programs to
become narrow and rote rather than broad and creative. A goal for the
next century will be to bring to educational programs in statistics the
same kind of creative vitality that marks the practice of statistics
among professionals in the field. This will require new emphases in both
content and pedagogy. Statistics education has caught the attention of
many; it now must prove itself by making effective use of this
opportunity to produce new generations of graduates that will not drown
in their world of data.
- October 4, 2000 (Fall Workshop)
- The Grammar of Graphics: Designing a System for Displaying
Statistical Graphics on the Web: Leland Wilkinson, SPSS, Inc.
- "The Grammar of Graphics" (GOG) is the
title of a recent Springer-Verlag book that encapsulates a new theory of
statistical graphics. GOG is based on an algebraic model. It contrasts
with the prevailing view toward classifying and analyzing charts by
their appearance - a view that one might call Pictures of Graphics
(POG). In POG, there are pie charts, bar charts, line charts, and so on.
Not only are most books and papers on graphics organized by chart type,
but so also are most charting programs and production libraries.By
contrast, GOG begins with a strong statement: there is no such thing as
a pie chart. A pie chart is a stacked bar graphic measured on a
proportional scale and transformed into polar coordinates.
Significantly, the description of simple charts in POG (such as a pie)
are more complex in GOG and seemingly complex charts in POG (such as
scatterplot matrices) are simple to describe in GOG. This contrast
between surface POG descriptions and deep GOG specifications exposes not
only previously unappreciated subtleties in the structures of common
charts but also the existence of charts not generally known. GOG is
ideally suited for designing a system for interactive Web graphics.
Examples will be shown using a Java production library called nViZn
(formerly GPL).
- September 6, 2000
- Epidemiological Causation in the Legal Context: Sana Loue,
Case Western Reserve University
- Reliance on epidemiological evidence has become
increasingly common in various legal contexts, including toxic tort
cases, criminal matters, civil lawsuits between individuals for alleged
harm, and actions to involuntarily quarantine individuals with specified
infectious diseases. However, the operationalization of causation
differs between law and epidemiology and the purposes of law and
epidemiology are quite different. These divergent methodologies and
purposes often result in the misuse and misinterpretation of
epidemiological principles and findings in the courtroom. Case examples
are used to illustrate these difficulties.
- June 7, 2000
- Flourishing or Floundering? Relief Pitching in Major League
Baseball: Rich Charnigo, Case Western Reserve University
- A manager in major league baseball has the
often-difficult task of deciding when and how often to switch pitchers
during the course of a game. Looking at the simultaneous decline in
pitching performance and increase in the use of relief pitching (and
perhaps with a few contests from last season in mind), one wonders if
relief pitching is being employed past the point of optimal
effectiveness. We will consider how relief pitching has changed over the
last thirty-nine years and formulate three linear models that will
relate the earned run average (a primary measure of pitching
performance) to the proportion of complete games (a proxy for the amount
of relief pitching). By considering a statistic designed to assess the
quality of a pitching change and the proportion of pitching
substitutions in 1999 contests that exceed a certain threshold value of
this statistic, we will assess the overall effectiveness of relief
pitching. With this finding and the results from the aforementioned
linear models, we will argue that relief pitching may now be
contributing to the very problem which it is designed to circumvent:
high scoring by the opposition.
- May 3, 2000
- Computer Generation of Magic Squares Using Minitab: Josephina
de los Reyes, University of Akron
- The purpose of this talk is to present a computer
method of generating a magic square using MINITAB®, a statistical
software. A magic square of order n is an n x n array of the integers
1,2,n2 so that the sum of entries in the n rows, n columns, and main
diagonals is a constant. Amid fascinating historical and recreational
aspects of magic squares, and theoretical questions asked about it when
regarded as a matrix, two ideas in particular caught this author's
interest. One idea is the fact that under certain restrictions, a magic
square oforder n may be constructed from two mutually orthogonal Latin
squares ("MOLS") of order n. Is this procedure reversible for
all n - under what conditions can MOLS be obtained from a magic square?
Initial results obtained by the author show that given a magic square
and a Latin square, another Latin square that is orthogonal is
derivable. The second idea comes from an article in electronic
engineering about the effectiveness of a dithering algorithm in color
printing that is based on a 3x3 magic square over that based on a "direct"
dithering algorithm.
- April 5, 2000
- Computing Multivariate B-splines: A Simulation Based Approach:
Nidhan Choudhuri, Case Western Reserve University
- Univariate B-splines played an important role, both
as a theoretical and practical tool, in dealing with polynomial splines;
its multivariate counterpart, despite having all the theoretical
properties of the univariate case, lacks application because of the
computational difficulties. Unlike the univariate case, where there is
an explicit form of the B-spline function, the multivariate B-spline is
only implicitly defined and needs numerical approximation. Some
computational procedures, based on a recurrence relation formula by
Micchelli (1980), are available today. But the computing time there is
too long and increases exponentially with the number of knots. In this
talk, we shall introduce a new simulation based procedure of computing a
multivariate B-spline function, which is less time consuming and easy to
implement. Theoretical results will also be presented to support the
validity of this procedure.
- March 1, 2000
- Likelihood Functions, Parametric Statistical Inference and
Mathematica: Daniel Cap, DMC Technology
The relationship between parametric probability
distributions and likelihoodfunctions plays a fundamental role in both
applied and theoretical statistics. The object of this talk is to show
how Mathematica, a modern mathematical modeling environment, can be used
to explore likelihood functions and make parametric statistical
inferences. We'll use simple examples, with binomial, normal and weibull
distributed random variables, to illustrate the key ideas. After this
introduction, we'll explore practical applications to reliability
engineering and robust (Taguchi)engineering design problems, where both
the location and scale parameters of the associated likelihood functions
are modeled with regression equations.
- February 2, 2000
- Recent Findings from Two Clinical Surveys: John Holcomb,
Youngstown State University
This presentation will discuss two recent projects
involving Dr. Ralph Rothenberg, MD of Forum Health Services, Youngstown,
OH. The first project involves determining if guidelines mailed to every
physician in the country by The American College of Rheumatology
impacted baseline and follow-up blood, kidney and liver testing of
patients given prescriptions of a non-steroidal anti-inflammatory
medication. The second project also involved Dr. Joan Boyd. Here we
investigated the effectiveness of health fair osteoporosis screenings.
Subjects identified to be at risk for osteoporosis by ankle bone density
screening were surveyed six months later to determine if the primary
physician was seen and treatment obtained. The talk will present the
results of these investigations and thoughts on future research in these
areas.
- January 5, 2000
- The Supreme Court's Decision on the Census: Dan O'Leary,
Marconi Medical Systems
On January 25, 1999 the US Supreme Court ruled on
a pair of lawsuits relating to the use of statistical methods for
apportion of the US House of Representatives. The court ruled that using
statistical methods for apportionment of the House of Representatives
violates the US Constitution. They also ruled, however, that current law
requires the Census Bureau to use statistical methods for other
purposes. The presentation reviews the Supreme Court's decision and
explains the issues and the Court's reasoning. It looks at the
Constitutional requirements for apportionment and the census including a
number of constitutional amendments in this area. The presentation
touches on the problem of fair apportionment, the legislation relating
to the Census, the undercount problem, the initial plan for Census 2000,
and the revised plan for Census 2000. Time permitting, we look at some
of the arguments for and against sampling.
- 1999 Talks
- December 1, 1999 (Cleveland Chapter Presidential Address)
- Acute Care for Elders: Stopping Functional Decline in
Hospitalized Elders: Linda Quinn, QED Industries
Patients age 65 and over account for approximately
37% of acute non-federal hospital admissions and 48% of inpatient days
in the United States. Functional decline is common in older adults
following an acute medical illness and hospitalization. Evidence
substantiates that at least one-third of patients age 70 and over lose
the ability to independently perform one or more activities of daily
living (ADL) after hospitalization for an acute medical illness, and
three months post-discharge, 40% of these patients still do not regain
preadmission functional status. Patients with ADL decline accompanying
an acute illness and hospitalization are more likely to have a prolonged
hospital stay, die in hospital, be newly institutionalized at discharge,
and be readmitted to the hospital post-discharge. The Acute Care for
Elders (ACE) Unit is a multifaceted intervention that integrates
geriatric assessment into the optimal medical and nursing care of
patients in an interdisciplinary environment. Designed specifically to
help patients maintain or achieve independence in self-care activities,
the ACE Unit embodies four key elements: a specially designed
environment (with, for example, uncluttered hallways, large clocks and
calendars, and carpeting); patient-centered care emphasizing
independence, including specific protocols for prevention of disability
and for rehabilitation; discharge planning with the goal of returning
the patient to his or her home; and intensive review of medical care to
minimize the adverse effects of procedures and medications. This talk
will discuss the series of randomized clinical trials that evaluated the
effectiveness of the ACE Unit intervention.
- November 3, 1999 (Fall Workshop)
- Logistic Regression - A Workshop: Mike Kutner, The Cleveland
Clinic Foundation
Data are said to be binary when each outcome falls
into one of two categories such as alive or dead, success or failure,
true or false. Binary outcome data occur frequently in practice and are
commonly analyzed using the logistic regression model. This workshop
will emphasize the practical aspects of modeling binary outcome data
using logistic regression, including checking the adequacy of the fitted
models. Several examples from the health sciences area are presented to
illustrate the techniques. Parallels between multiple linear regression
modeling and multiple logistic regression modeling will be presented
throughout the workshop. Therefore, attendees of this workshop are
expected to be familiar with multiple linear regression modeling
techniques.
- October 6, 1999
- Optimal Small Response Surface Designs: Tena Katsaounis, MS
Three level factorial designs will be discussed
that are suitable for small second order designs. The best choice of
potential design points will be discussed under the criterion of
minimizing the generalized variance of the parameters in the model. Two
methods will be illustrated that yield designs with different resolution
for the main effects and two factor interactions. Both methods involve
the use of Partially Balanced and PB1 arrays. The Extended Partially
Balanced Array will be defined as a generalization of PB.
- September 8, 1999
- Handicapping Systems for Sailboat Racing: Paul Mathews
Wherever there are sailboats in the water there
are sailboat races. There are almost as many race scoring systems as
there are different kinds of sailboats. When boats that are racing are
all the same design (one design racing) or are very similar in design
(box rules) then scoring is easy and accurate. However, most racing
fleets contain a mixture of boats. In a single race it's not unusual to
find boats that run from 20 to 50 feet long, that weigh from 2500 to
30,000 pounds, that race with 3 to 15 people, and that cost from $3000
to $300,000. Under these diverse conditions performance handicapping
systems have evolved so that everyone has a chance (or is supposed to
have a chance) to win. Paul will use video clips to demonstrate the
scale of the handicapping problem. He will discuss the committee driven
handicapping systems that are based on elapsed time (Time-On-Time) and
course length (Time-On-Distance) and the ratings systems that are based
on aero- and hydrodynamic computer models (velocity prediction
programs). Then he will present a new rating system that is based on the
results of computer physical modeling but is refined with actual race
data. Paul will also talk about some of the technological developments
that will affect rating systems in the next five years.
- June 2, 1999
- Optimal Experimental Design in Poisson Impaired Reproduction
Studies: Jennifer Huffman, The Lubrizol Corporation
Impaired reproduction experiments are a class of
studies involving Poisson responses that are functions of concentrations
of toxicants, chemotherapy drugs, or other substances. Factorial-like D,
Ds, and interaction optimal designs are demonstrated for models
involving interaction through k factors. Augmentations of these designs
that result in desirable lack of fit properties are discussed. The
augmentation contains "center runs" that are analogous to
standard center runs in factorial designs for linear models. In
addition, fractional factorial designs are detailed along with their
alias structure. Robustness properties are addressed as well.
- May 5, 1999 (Joint Dinner Meeting at the University of Akron)
- Proportional Hazards Models With Informative Censoring: P.V.
Rao, University of Florida
A modification of the proportional hazards model
is proposed for informatively or randomly censored times to two types of
events -- a primary event and a followup event. The proposed model
treats informative censoring as a type of risk in a competing risks
setup and incorporates suitable parameters to describe the conditional
probability of failure given the subject is not informatively censored.
Inferences about the parameters in the model can be based on standard
partial likelihood theory. The model is used for analyzing some data on
waiting time to bone marrow transplantation (primary event) and time to
relapse or death after transplantation (followup event) for leukemia
patients.
- April 7, 1999
- Careers in Statistics: the Real World A Panel Discussion:
Susan Cowling, The Lubrizol Corporation; David Nelson, The Cleveland
Clinic; Patricia Cirillo, Cypress Research Group
- The panel presentation will be from 4:00pm to
5:00pm. The panel consists of three local statisticians who are employed
in different application areas. They will discucss: What do I do? What
types of analyses do I run? What type of degrees are required/useful?
What skills are important? Salary and Job market?
- March 3, 1999
- A Unified Regression Approach for Fixed Effects ANOVA Models with
Missing Cells: Mike Kutner, Cleveland Clinic Foundation
Many standard statistical software programs claim
to "handle" fixed effects ANOVA models when some of the cells
do not contain data (missing cell problem). Simple examples using SAS,
SPSS, and BMDP will be given documenting how these programs "handle"
the missing cells. Surprisingly, these computer packages generally
produce strange results. The sources of these difficulties will be
delineated. A unified full-rank regression cell means model approach
will be presented as a definitive solution to this problem. Experimental
design models, such as the balanced incomplete block design, will be
shown to be special cases.
- February 3, 1999
- Using Economic Designs for Multivariate Control Charts:
Thomas Love, Case Western Reserve University
The economic design of control charts means making
rational decisions about several parameters, including control limits,
sample (subgroup) sizes, sampling intervals, and degree of data
smoothing in light of a model for the costs and time associated with
monitoring and controlling a process. Technological advances have
sparked interest in multivariate process control methods - which allow
for the simultaneous study of several quality characteristics. The
Multivariate Exponentially Weighted Moving Average (MEWMA) control chart
is especially attractive to practitioners looking for methods that
effectively detect small shifts in a process mean vector. We discuss the
use of economic designs for multivariate control charts, focusing on the
MEWMA. This presentation is the result of joint work with Kevin
Linderman, at the University of Minnesota.
- January 6, 1999
- "Actuarial" vs. "Actual" Analyses:
Accounting Simultaneously for Multiple Competing Risks of Events:
Eugene Blackstone, Cleveland Clinic Foundation
Typical life tables (generically called "actuarial"
tables, be they related to survival of patients or reliability of
machines) address the distribution of times to a single event. In some
settings, however, other events may occur prior to the event of interest
that effectively remove a patient or item from the possibility of
experiencing the event of interest. For example, one may wish to study
the need for additional procedures following a heart bypass operation.
However, death may occur before the need for an additional procedure.
This usually does not affect the estimates of the probability of
reintervention, but it does affect the "actual" number of
reinterventions that will be observed in patients across time. Or a
heart valve manufacturer may know that there is a high probability that
a valve will deteriorate over a period of many years, but if these are
used in elderly people, the number of actual valve replacements for
deterioration may be low because of natural attrition from other causes.
In the late 18th century Daniel Bernoulli presented the mathematics for
multiple competing events, using it to predict the impact on survival of
a population were smallpox to be eradicated. This led to multiple
decrement life tables in demography and the general theory of competing
risks in statistics. This talk will be introductory in nature using
buckets with different sized leaks as a motif, providing motivation for
the technique in several medical settings, examining the appropriateness
of the methodology to different questions being asked, and briefly
introducing both nonparametric and parametric estimation methods.
- 1998 Talks
- December 2, 1998 (Cleveland Chapter Presidential Address)
- Five Randomized Clinical Trials of Abciximab During Percutaneous
Coronary Intervention: Shelly Sapp, Cleveland Clinic Foundation
Platelet thrombus formation, resulting from
platelet activation, adhesion and aggregation, predisposes patients to
the development of ischemic complications after percutaneous coronary
interventions (PCIs). Clinical evidence suggested that sustained
platelet inhibition after PCIs may reduce the occurrence of
post-hospital events such as myocardial infarction and coronary
revascularization. Recently, a new class of platelet antagonists
directed against the platelet membrane glycoprotein IIb/IIIa receptor
has undergone extensive clinical testing. One of these agents, Abciximab
(ReoPro, Centocor), blocks this receptor, thus preventing platelet
adhesion and aggregation. Between 1991 and 1998, five randomized,
placebo-controlled clinical trials of Abciximab during percutaneous
coronary intervention involving a total of 9038 patients have been
completed. This talk will describe the motivation behind the design of
these trials as well as some of the major results.
- October 29, 1998 (Dinner meeting)
- Geographical Trends in Cancer Mortality: Using Spatial Smoothers
and Methods for Adjustment : Karen Kafadar, Ph.D., University of
Colorado-Denver
Mapping health-related data can lead to important
insights and generate hypotheses about causes and potential effects.
Such data are commonly adjusted for the variables age and gender, so
that inferences are not influenced by these obvious factors. In a
similar fashion, data for certain diseases ought to be adjusted for
known risk factors. One method of adjustment is suggested here, and
insights from the adjusted data are enhanced by smoothing the data in
the two dimensions (longitude and latitude). The process of adjustment
and smoothing is illustrated on three sets of cancer mortality data:
lung cancer (using urbanicity as the adjustor), prostate cancer in
nonwhites (using percent African-American as the adjustor), and melanoma
among whites (using latitude as the adjustor). In each case, the maps of
the adjusted rates indicate patterns that are worthy of investigation
and may contribute to the generation of hypotheses and further
understanding of the etiology of the diseases.
- October 7, 1998
- Testing For Equivalence of Diagnostic Tests: Nancy
Obuchowski, Ph.D., Cleveland Clinic Foundation
Studies comparing the diagnostic accuracy of
clinical tests are common, particularly in the field of radiology.
Accuracy is defined in terms of the test's sensitivity, specificity, or
indices associated with the Receiver Operating Characteristic (ROC)
curve. In comparing two tests, we are often interested in determining if
a new test has similar accuracy as an existing test, i.e. `Are the two
tests equivalent?'. We propose two criteria for defining diagnostic
equivalence and methods for testing equivalence. The criteria are
referred to as `Population Equivalence' and `Individual Equivalence';
they are modifications of criteria used for assessing equivalence
between generic and standard drugs. The proposed methods are illustrated
for a study comparing the diagnostic accuracy of digitized mammographic
images to original film. The digitized images are easy to store and
retrieve, but the digitization process may result in a loss of accuracy.
We test whether the accuracy of the digitized images is equivalent to
film and whether the management of individual patients will be impacted
if digitized images replace films.
- September 9, 1998
- Is Rank Transformation Method a bad idea?: Guang-Hwa "Andy"
Chang, Ph.D., Youngstown State University
The rank transformation (RT) refers to the
replacement of data by their ranks, with a subsequent analysis using the
usual normal theory procedure, but calculated on the ranks rather than
on the original data. This idea was originally suggested by Lemmer and
Stoker (1967) and advocated by Conover and Iman. The availability of
statistical packages for parametric tests makes the rank transformation
method appealing. SAS had also added this option in their package.
However, Blair, Sawilowsky and Higgins (1987) showed that, for 4x3
factorial designs, a severe inflation in Type I error of the RT
statistics for testing interaction is observed as either the cell size
becomes large or the row and column main effects are large. It was a
huge disappointment. Is the rank transformation method a bad idea? Some
research results after the simulation study by Blair et al. will be
presented in this talk.
- June 3, 1998
- Genetic Mapping of Complex Human Diseases: Jane M. Olson,
Ph.D., CWRU
In recent years, genetic study of complex human
diseases has increased dramatically. Most human diseases are now
believed to have some genetic component, and considerable effort is
being made to find and study the genes involved. As a result,
statistical methods used to find disease genes are receiving a great
deal of attention, and statistical mapping methodology is evolving
rapidly. In this talk, I will provide an overview of genetic mapping
methods, focusing primarily on genetic linkage analysis. I will first
explain concepts in genetic inheritance that statisticians exploit in
genetic mapping, and introduce relevant terminology. I will then explore
the two main types of genetic linkage analysis: model-based and
model-free. In model-based linkage analysis, one estimates a genetic
model of inheritance for the disease using pedigree likelihood methods,
then fixes the model in subsequent estimation of the linkage parameter
that describes the relationship between the inheritance of disease and
marker loci. In model-free linkage analysis, a smaller set of parameters
that are functions of the genetic model and the linkage parameter are
estimated, so that the genetic model of the disease need not be known
prior to analysis. Instead, sharing of marker alleles between related
individuals is exploited. I will discuss the relative usefulness of
these approaches in practical genetic mapping problems, and provide some
discussion of future directions.
- May 6, 1998
- Good Apple? Sampling Biases: Jiayang Sun, Case Western
Reserve University.
In practice, data are more often from "hell"
thaom "heavn fren". They may come with missing values,
censored or truncated observations, outliers and/or from a biased
sample. If missing values are missing at random (and are not too many),
deletion or an imputation procedure may be used to clean up the data
before analyses. If whether a data point is missing depends on the true
value, the data have come from a biased sample. In the presence of
sampling biases, standard procedures often fail badly. In this talk we
present some fun examples with conclusions that were drawn ignoring
biases, and illustrate why some cases with censoring or truncated
observations may be considered from a biased sampling. We then offer
some simple solutions and go into the author's current research in this
area.
- March 24, 1998 (Joint Dinner meeting with Case Western Reserve
University)
- Follow-up Designs that Make the Most of an Initial Screening
Experiment: Robert Mee, Department of Statistics at University of
Tennessee in Knoxville.
Industrial experimentation is often sequential,
with initial screening experiments followed by other stages of
experimentation. Common alternatives for subsequent experimentation
include the path of steepest ascent, augmenting an initial fractional
factorial via foldover, and adding axial and center points to complete a
central composite design. This talk will focus on two other
alternatives: augmentation via semifolding and non-central composite
designs. In each case we find opportunity to use estimates from the
initial experiment to direct location of the follow-up design.
- March 4, 1998
- Navigating the Net: Susan E. Branchick, Ricerca
The Internet contains a wealth of information, but
locating it can be a frustrating experience. This talk will present tips
and techniques to make your experience on the Internet a smoother ride.
Topics will include how to subscribe to a discussion group, work within
frames on the WWW, search for information and handle documents. It will
conclude with an overview of some statistical related sources.
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- February 4, 1998
- Statistical Literacy and Statistical Competence in the 21st
Century : David S. Moore, 1998 President, American Statistical
Association
Educated people face a new environment at
century's end: work is becoming intellectualized, formal higher
education more common, technology almost universal, and information (as
well as mis- and dis-information) a flood. In this setting, what is
statistical literacy, what every educated person should know? What is
statistical competence, roughly the content of a first course for those
who must deal with data in their work? If the details are automated,
are the concepts and strategies that guide us enough to maintain "statistics"
as a distinct discipline?
-
- January 7, 1998
- Statistical Opportunities and Job Search Fundamentals: Greg
Jarecki, Trilogy
This presentation will focus on three areas:
career trends in the statistical field, elements of successful career
planning, and fundamentals of job hunting. Included with career trends
are career opportunities, skill requirements, and salary ranges for
various statistics professionals. Included with job hunting fundamentals
are resume preparation, and the differing perspectives of job candidates
and employers.
- 1997 Talks
- December 3, 1997 (Cleveland Chapter Presidential Address)
- Quantitative Investing: Bill Katcher
Is the stock market just another process? Yogi
Berra says, "You can see a lot just by looking." I believe
that a lot can be learned with basic statistical methods like regression
analysis, data plotting, and time series analysis. Spreadsheets are the
tool that make it possible for the individual investor to monitor the
process in near real time. There are two parts to the investment
decision. First, what's the overall market direction and second, what
specific investments are the best at this time. I hope to be able to
give you some new ideas in both areas.
-
- November 5, 1997
- Designing for Better Data, Timely Analysis, and Effective
Reporting: Mark Martin, Chiron Diagnostics Corporation
As statisticians, we too frequently encounter the
frustration of spending more time than we like cleaning and preparing
data. Ideally, we would like to spend the majority of our time designing
for, analyzing, and reporting from good data. Doing so requires a good
balance of foresight, collaborative planning, information sharing,
tools, continuous learning, and communication skills. Experiences from a
fast-paced project will be shared, including successes and pitfalls.
While specific practices vary in different environments, certain basic
principles apply across workplaces. An extensive bibliography of good
references (for both statisticians and non-statisticians) will be
provided. As a specific tool, the use of "data flow diagrams"
will be demonstrated.
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- October 1, 1997
- Rank Analysis of Means: Dan Sommers, General Electric
The typical non-parametric procedure for analyzing
a one-factor design is the Kruskal-Wallis test. An alternative
procedure, using a rank approach to the one-factor analysis of means,
will be presented.
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- September 10, 1997
- Testing for Treatment Effects which are Increasing Functions of
the Rate of Disease Progression: Tom Greene, Cleveland Clinic
Foundation
Clinical trials in chronic disease populations are
often designed to test whether a treatment intervention slows disease
progression as assessed by the slope of repeated measurements of a
marker of disease severity. For continuous markers, mixed effects models
are generally used to test for additive treatment effects on the mean
slope, implicitly assuming that the treatment effect for each patient is
independent of that patient's progression rate. However, a close
examination of the hypothesized mechanisms of the treatment often
suggests that the clinical hypothesis can be better formulated by a
treatment effect whose magnitude increases as a function of the
progression rate. We introduce a mixed effects model in which the
treatment effect is proportional to the rate of progression for patients
with negative slope, and equal to zero for patients whose slope is
non-negative. An estimated least squares approach is proposed for
estimation and hypothesis testing in this setting. We show that use of
standard additive analyses can lead to markedly lower power than the
proposed procedure when the treatment effect increases with the effect
size. We also examine time-to-event analysis based on the time to a
specified clinically meaningful reduction in the outcome marker as a
practical alternative to mixed models when increasing treatment effects
are considered likely. These approaches are illustrated with examples
from clinical trials in renal disease.
-
- June 4, 1997
- Projection Methods for Generating Mixed-Level Fractional
Factorial and Supersaturated Designs: Alonzo Church, Jr.
The definitions of resolution and projectivity
have been used to develop an algorithm to find mixed-level fractional
factorial designs. Some of the designs differ from standard designs and
have superior projection properties. In addition their least squares
properties are often superior. In his presentation, Mr. Church will
describe the algorithm and give details on some useful alternative
designs.
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- May 7, 1997
- Forensic Economics: John F. Burke, Ph.D.
In his talk entitled "Forensic Economics",
Dr. Burke will concentrate on the ways statistics and probability can be
statistical evidence in jury trials, he will use actual cases involving
racial discrimination and the asbestos industry as examples.
-
- April 2, 1997
- Alternative Control Charts: Tom Ryan, Case Western Reserve
University
Traditional methods for determining control chart
limits have appealed to the Central Limit Theorem when an Xbar chart is
used and to the normal approximations to the binomial and Poisson
distributions when attribute charts are used. Unfortunately, these
approaches can produce very poor results. Recent research on improved
techniques for measurement and attribute data will be presented,
including methods developed by the speaker. The control chart panel
discussion that is appearing in the April issue of the Journal of
Quality Technology will also be briefly
discussed.
-
- March 5, 1997
- Cleveland Technical Societies Council: Fred Lisy, CTSC
The Cleveland Technical Societies Council (CTSC)
brings together the members of the technical, and engineering societies
in Northeastern Ohio to: Provide a forum for discussion and a vehicle
for action on matters of mutual concern and interest; Serve as a focal
point for contact between industry and society at large with the
technical and scientific community, Promote intersociety communications,
professional interchange of ideas and coordination of society
activities; Promote interest in and encourage careers in the scientific
and technical professions through career guidance and other educational
programs. The CTSC has approximately 50 member societies and
associations such as American Association of Cost Engineers (NE Ohio
Section), American Institute of Aeronautics and Astronautics, American
Institute of Chemical Engineers, the American Society for Information
Science, the American Society for Quality Control (Cleveland Section),
the Cleveland Computer Society, the Cleveland
Engineering Society, Society of Fire Protection Engineers and the
Cleveland Chapter of the American Statistical Association. The CTSC
program's include: Technology infrastructure such as educational
programs complement, education program database, career day, science
fair mentoring and local student programs; Technology transfers such as
consortiums and R&D partnerships issues, technology policy forum and
regional engineering technical symposiums; Technology development such
as forums for technology awareness, public awareness of technology and
industry-government R&D partnerships.
-
- February 5, 1997
- Update on the Data Coordinating Center and the African American
Study of Kidney Disease and Hypertension: Jennifer Gassman,
Cleveland Clinic Foundation
The African American Study of Kidney Disease and
Hypertension (AASK) is a randomized clinical trial sponsored by the
National Institute of Diabetes, Digestive and Kidney (NIDDK) Diseases of
the NIH. There are 21 Clinical Centers across the United States,
including one in Cleveland at Case Western Reserve University. The Data
Coordinating Center is in the Deparment of Biostatistics at the
Cleveland Clinic. Statisticians working on the study include Mike
Kutner (Principal Investigator), Jennifer Gassman, Tom Greene, and Shin
Ru Wang. In this 3x2 factorial design study, participants receive 1 of 3
blinded antihypertensive agents (ACE inhibitors, beta blockers, or
calcium channel blockers) and either usual blood pressure control (MAP
of 102 to 107 mm Hg) or low blood pressure control (MAP <92 mm Hg),
where MAP = 1/3 systolic + 2/3 diastolic blood pressure. The primary
outcome variable is rate of change in glomerular filtration rate (GFR),
a measure of kidney function. Data are entered directly from the
clinical centers into a central Oracle database, using the Internet. The
study has been going on for about two years, and there are about four
more years to go. In this non-technical
presentation, the speaker will give an update on what the Data
Coordinating Center is doing and how the AASK Study is progressing.
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- January 8, 1997
- Response Surface Methods for Costly Noisy Data: Art Holmes
The presentation will include a quick review of
the concepts of response surface methods. The review will be followed by
the rationale of a specialization to high efficiency central composite
experiments for costly noisy data. For 2 through 8 independent
variables, design tables will present the efficient numbers of center
points that can be distributed among the blocks. The numbers of center
points vary from 2 to the number of hypercube blocks plus 4. The
tables list the star point radii for orthogonal blocking.
- 1996 Talks
- December 4, 1996 (Cleveland Chapter Presidential Address)
- Presenting Results - Using Tabular Displays Effectively: John
Schollenberger, Ricerca
Graphical displays are important, but, we also
need to give careful consideration to our use of tables. The design and
layout of the tabular displays in a report can also help or hinder a
client's understanding of the results. My recent experiences suggest
that, more often than not, tables are used only to provide a listing,
either of raw data or of summary statistics and results, with little
thought as to their digestability. That is, we don't consider how that
table, or a different table, might be better used to assist the reader
in understanding the results or believing the conclusions that are
drawn. I will step through a suggested redesign of several tables.
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- November 6, 1996
- Inference About the Change-Points in a Sequence of Random
Vectors: Arjun K. Gupta, Bowling Green State University
In this talk, the change-point problem is
reviewed. Then, testing and estimation of multiple covariance change
points for a sequence of m-dimensional (m>1) Gaussian random vectors
by using Schwarz information criterion (SIC) is studied. The unbiased
SIC is also obtained. The asymptotic null distribution of the test
statistic is also derived. The result is applied to the weekly prices of
two stocks (m=2), Exxon and General Dynamics, from 1990 to 1991, and
changes are successfully detected.
-
- October 2, 1996
- The Meaning of Analysis of Means: Edward G. Schilling,
Rochester Institute of Technology
The Analysis of Means is becoming increasingly
well known. It is a method for the graphical analysis of the averages of
proportions resulting from a designed experiment.The procedure has been
applied to a variety of experiments including crossed and nested fixed
effects models, balanced incomplete blocks, split-plot, etc. It is
especially useful as a communication tool in an industrial environment
since it is based on Shewhart control chart concepts. The background and
use of this approach will be discussed in terms of industrial examples.
- September 4, 1996
- Constructing a Deterministic Model of an Epidemic Process When
All Parameters Must be Estimated : John Neill, the City of Cleveland
Department of Public Health
It is often impossible to obtain the parameters
required to construct a classical deterministic model of an epidemic
process since the number of people at risk and contact rate are usually
unknown. New diseases, such as AIDS, may have no known incubation
period. A technique is presented for using observed incidence to
estimate all the parameters necessary to make deterministic models of
diseases like AIDS or hepatitis A. The method also produces estimates
of incubation distributions for AIDS and hepatitis A comparable to those
in the medical literature.
-
- June 5, 1996 (Joint Meeting with the Cleveland SAS Users Group)
- Statistical Quality Control Using the SAS System : Dennis
King, STATKing Consulting
This presentation will be divided into two parts.
The first part discusses the seven tools of quality with emphasis on the
SAS software and programming useful for implementing these tools. The
second part of the presentation focuses on the control chart and the
statistical methodology surrounding the use of this tool.
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- May 1, 1996
- Pros and Cons of Cutpoints: Jane Goldsmith, Health Sciences
Biostatistics Center at the University of Louisville
Authors have noted the disadvantages of
dichotomizing or taking cutpoints in the data. Some textbooks and
educators still advise students to dichotomize in order to use
convenient Chi-square statistical analysis. Statistical packages make
this transformation easy. This talk summarizes the costs of
dichotomization, considering efficiencies of Chi-square versus t-tests,
Mann-Whitney U tests, Regression and Correlation Analysis, and Spearman
Correlation Analysis. Practical examples will be given for cases when
dichotomization is desirable and undesirable from a power standpoint.
Discussion of logistic regression and implications for the use of CART
are included.
-
- April 3, 1996
- Statistician Meets the Customer: Mark Martin, Ciba Corning
On an automated immunochemistry system which runs
more than 25 different blood tests, customer satisfaction can vary with
the performance of the assays that a particular hospital or laboratory
runs on the instrument. During assay development, one challenge is to
predict the customer complaint rate if the assay were to be released at
a given point in time, and to provide indicators of when an assay meets
release-for-sale goals that will please the customer. As a part of this
effort, interviews were conducted at several customer sites.
- March 6, 1996
- On The Importance of Assessing Measurement Reliability When
Fitting Regression Models : Leon J. Gleser, University of Pittsburgh
In many regression contexts, some predictor
variables are measured with error, or replaced by proxy measurements for
reasons ranging from convenience to cost. In such cases, adjustments to
classical least squares slope estimates may be needed to correct for
bias. These adjustments require knowledge about the parameters of the
model that is often not supplied by the data. It is argued here that the
required knowledge concerns the reliability matrix of the vector of
measured predictor variables. Ways to design auxiliary experiments to
obtain reliability information, and to combine such information with
information available from published studies, are discussed.
- February 7, 1996
- A Paradigm Shift in Statistical Consulting: Mukul Mehta,
Quality Sciences, Inc.
Eighties show TQM emerge as a major movement in
American industry. The TQM wave is now followed by reengineering and
corporate right sizing. Staff groups are out of fashion or under intense
pressure to produce more with less. This is an excellent opportunity for
an industrial statistician to prosper or perish. Time to market is
becoming a dominant force in the market place and will forever continue
to be. For professional statisticians to survive and prosper we need to
rethink how TQM reengineering and time to market affect our profession
and what we need to do to respond to challenges. We need a paradigm
shift. Information technology is becoming the key component of
reengineering and has the potential of forever changing
the traditional approach to statistical consulting. QSI has developed a
software-based approach to enable large groups of scientists and
engineers to take advantage of the power of statistical thinking without
the pain. Through slides and software, Mukul
will illustrate issues, challenges and opportunities that lie ahead.
- January 10, 1996
- Making Statistics Understandable for Students and Industry:
Paul Mathews, Lakeland Community College
Paul's students come from industry, most with 5 to
20 years experience as machine operators, technicians, or supervisors.
They have a growing interest in quality engineering but, unfortunately,
very limited math skills. They quickly come to the opinion that people
write textbooks to make money (based on their experience in the
bookstore) and impress their friends. Paul will describe some of the
notational conventions he has found well received by the students, and
show some of their favorite graphical presentations.
- 1995 Talks
- December 5, 1995 (Cleveland Chapter Presidential Address)
- Portrait of a Cleveland Clinic Foundation Statistician: Lisa
Rybicki, The Cleveland Clinic Foundation
George Williams arrived at the Cleveland Clinic
Foundation in August 1980 and the Department of Biostatistics was born.
George began to expand the department in 1981. Now, 15 years later, the
department employs 80 people, almost half of which are statisticians.
The mission of the department is to excel in the conduct of medical and
methodological research, and to promote the proper use of statistics and
epidemiological methods. The department fulfills this mission through a
wide variety of collaborative and educational activities. Lisa will
describe the organizational structure and work environment, illustrate
the mechanisms used to fulfill their mission, and examine the role of
the collaborative biostatistician in this dynamic environment.
- November 1, 1995
- Implementation of Total Quality Management in an R&D
Environment: Dennis J. Keller, RealWorld Quality Systems
This talk gives an overview of the unique
challenges and solutions associated with implementing Total Quality
Management (TQM) in a technical or R&D environment. It begins with
defining TQM, its goals and objectives, and how these differ from their
well understood counterparts in manufacturing and general business
arenas. Next, a generalized global framework of hierarchical "systems"
is presented, which when taken as a whole, represents the "System"
of TQM in R&D. Each system in the hierarchy is then explored in only
moderate detail to demonstrate its critical function in the global
system. The system hierarchy are: 1) Project/Problem Solving, 2) the
Researcher's Personal TQM System, 3) the Branch/Group/Division TQM
System, and 4) the overall TQM System. Lastly, a short overview will be
given on strategies for actual implementation and managing for change.
- October 11, 1995
- Product Optimization in the Chemical Additives Industry:
Carlos L. Cerda de Groote, The Lubrizol Corporation
Very often in industrial practice there is an
interest in understanding how to control and optimize a response. Two
optimization examples are given. The first example deals with
formulating practice. One wants to know how a blend's composition
affects viscosity. The goal is to obtain cost effective blends that
satisfy viscometric requirements. Predictive viscometric equations are
fitted to data and then used together with constraints and a cost
function to obtain minimum cost formulations. The second example deals
with a predictive model for the molecular weight distributions (MWD) of
blends of polymers. Engine performance depends on the MWD of the
polymer(s) used with the additive chemistry. Control of this parameter
also leads to opportunities for optimization within the formulation
framework. In both examples the optimization was done with Microsoft
Excel.
- September 6, 1995
- News and Numbers: How Reporters Can Tell Facts From Lies, How You
Can Help: Victor Cohn, Research Fellow of ASA
Journalists and the public are often confused by
constantly conflicting "they say's" about health, science, the
environment and many other subjects. How can you help reporters report
facts, or the best facts you can muster, correctly? Tell them about
uncertainty. All you can give them is the best estimate at the moment.
Tell them about the use of probability, the power of large numbers, the
pitfalls of variability and the dangers of bias. Some basic rules for
dealing with the media and informing the citizenry will be discussed.
Remember that candor builds credibility.
- June 7, 1995
- Statistics in the Insurance Industry: James Jiang,
Progressive Insurance
Insurance rates are mainly determined by the past
loss experience. Statistical methods have been employed to analyze the
historical data to set up adequate rates. even though there are some
differences in reasoning between a casualty actuary and a statistician,
they often arrive at similar conclusions. Following an introduction to
automobile insurance rate making, James will demonstrate how statistical
science can be applied to reach some important results in credibility
theory and risk classification. The alternative reasoning by the
casualty actuaries will also be presented.
- May 3, 1995
- Robust Methods for the Detection of Linkage and the
Identification of Genes for Complex Disorders: Deborah V. Dawson,
Case Western Reserve University
Genetic linkage refers to the tendency of two
different genes to be inherited together if they are located
sufficiently close together on the same chromosomal strand of DNA.
Modern molecular biology has put at our disposal a vast array of genetic
markers, located at intervals throughout the human genome. The
establishment of genetic linkage between a known marker system and a
putative gene for a disorder is generally regarded as the ultimate
statistical evidence for a genetic component in the disease etiology.
Statistical methods for the detection of linkage include maximum
likelihood based approaches and the so-called robust or model-free
approaches. The latter are usually based on pairs of relatives, and in
contrast to the likelihood based methods, do not require specification
of the mode of inheritance for the disease trait.
- April 12, 1995 (Joint dinner meeting with the ASQC)
- Quality is Personal: Harry V. Roberts, University of Chicago
Personal quality is the application of quality
ideas to your job (and even to your life). Personal quality does not
directly tell you how to do your job better. Rather, it offers a
philosophy and methodology for learning how to do it better. Personal
quality helps people to perceive and remove waste from their own jobs.
As a result, they can achieve both continuous improvement and
breakthroughs. Some potential gains to the individual care increased job
satisfaction, education in quality management concepts and tools, and
assessment of the usefulness of quality management concepts based on
direct experience rather than the claims of others. Personal quality
differs from traditional time management although it may help to make
better use of time management tools. Personal quality is not just
another self-improvement program like speed reading, public speaking, or
memory development, although these skills can
lead to improvement of personal quality.
- March 1, 1995
- Statistical Graphics: Innovate! Show the Data: Ralph O'Brien,
The Cleveland Clinic Foundation
Today's computing tools allow us to create
statistical graphics that are customized to the particular hypotheses,
research designs, measures, and conclusions at hand. This demands higher
levels of "statistical graphicacy" from both authors and
readers. We should be open to innovation and tolerant of some
complexity. As Tufte proclaimed, "Above all else, show the data".
In clinical trials, for example, we must strive to show how patients
respond to treatments, so that we can see both general tendencies and
individual variation. These points will be discussed by studying
examples.
- February 1, 1995
- Statistics and the Law: Lynn D. Sivinski, Case Western
Reserve University
In spite of the apparent disparity between the two
fields, there are several areas where statisticians can assist lawyers
in litigation. Lynn will discuss a few of these subject areas and how
the statistical tools are used in making arguments. She will also
discuss how legal standards of proof and scientific ones differ.
- January 11, 1995
- Quantitative Literacy: A Data Driven Curriculum: Jeff Witmer,
Oberlin College
One of the many spin-offs of ASA's Quantitative
Literacy program is the Data Driven Curriculum Project. The goal of this
project, which is supported by an NSF grant, is to develop materials for
mathematics courses taken in grades 7-12. These materials are intended
to be used within existing courses in algebra, geometry, etc. The
Cleveland Chapter gas been very active in supporting the QL program for
several years and Jerry Moreno has planned a 1995 summer workshop based
on the Data Driven Curriculum materials. During this talk we will look
at the project and some of the activities within it.
- 1994 Talks
- December 7, 1994 (Cleveland Chapter Presidential Address)
- The Ethical Statistician: Linda Quinn, Case Western Reserve
University
A working definition for unethical professional
behavior as a statistician is any action intended to mislead, misinform,
or mask information without making clear the relevant limitations of the
outcome and its presentation. From incorrect analyses and violated
assumptions to fraudulent data and misrepresented results, ethics and
statistics interact.
- November 2, 1994
- Interim Analysis for Clinical Trials: A Generalized Spending
Function Approach: Hussein R. Al-Khalidi, The Proctor & Gamble
Company
- In most clinical trials, patient recruitment occurs
over a period of years and data or information from the trial
accumulates steadily throughout it's duration. The trial should involve
the smallest number of patients required to reach a firm decision. Group
sequential methodology in which groups of patients are analyzed
periodically is an approach that is economical, ethical and allows for
steady accumulation of data. Boundaries for maintaining a fixed
significance level will be discussed. Since interim analyses will be
conducted at times other than at those planned, a proposed generalized
spending function will be used to generate discrete boundaries. The
optimality property of the proposed function will be discussed.
- October 5, 1994
- Beyond the Shewhart Paradigm: J. Stuart Hunter, Princeton
University
- In today's 'bits and pieces' assembly industries
modern instrumentation allows the precise measurement of almost every
item produced. The consequence is time series data not unlike that
obtained in the continuous process industries. The basic concepts
underlying the popular Shewhart charts are thus often inappropriate when
applied in an assembly industry environment. This lecture proposes an
alternative, yet simple model that can extend the usefulness of the
Shewhart methodology and, if desired, lead to immediate active control
of the industrial process.
- September 7, 1994
- Robust Data Analysis Made Simple: Tom G. Filloon, The Proctor
& Gamble Company
- In many practical situations an observed data set
may contain extreme values (heavy tailed/contamination) that may cause
one to be leery of normality based conclusions. Hence a robust analysis
may be in order. However, a more efficient analysis might be obtained by
something other than a log or rank transformation approach. Tom will
briefly outline various robust methods and then discuss M estimation in
some detail. Implementing a pseudo value approach, he will show how M
estimation can be carried out via simple least square (such as in SAS)
and the utility of this method will be demonstrated using several real
examples.
- June 1, 1994
- Some Interesting Regression Modeling Examples: Mike Kutner,
The Cleveland Clinic Foundation
- As a consulting statistician one sometimes comes
across data sets that are not routine textbook examples. Three such
examples will be presented and solutions proposed. Each of these
examples are from "real life" data sets. In addition, all
three examples are relatively small data sets with only two to four
potential predictor variable that need to be modeled.
- May 4, 1994
- Reporting and Reviewing Research Results: Thomas Lang and
Michelle Secic, The Cleveland Clinic Foundation
- No one can deny the existence of a long standing
problem in the medical literature; errors and omissions in reporting
statistical results. The speakers are developing a comprehensive set of
guidelines for presenting statistical information in biomedical
publication entitled Reporting Statistical Information in Biomedical
publications: A Guide For Authors, Editors and Reviewers. The purpose of
the guide is to aid in recognizing, understanding a properly reporting
statistical analyses. The guide is being developed from a thorough
review of the literature. It will not serve as a statistics text but
will function as a reference designed to help authors, journal editors,
medical students and peer reviewers understand and correctly present
statistical information.
- April 13, 1994
- Practical Issues and Difficulties in Coordinating a Stroke
Treatment Trial - A Statistician's Perspective:Robert Woolson,
University of Iowa
- In Prof. Woolson's talk a particular trial is
discussed with emphasis on issues such as distributed data entry,
reliability assessment, training an monitoring.
- March 2, 1994
- Getting Started with PROC MIXED: Kristen Latour, The SAS
Institute
- This presentation introduces PROC MIXED using
examples that include split-plot designs, repeated measures data and one
way ANOVA with unequal variance. The GLM and MIXED procedures are
compared in terms of syntax, output and interpretation. An overview of
SAS statistical modeling procedures in included.
- February 2, 1994
- Multivariate Data Analysis with New Visualization Methods:Vladimir
Grishin, Case Western Reserve University
- Experienced statisticians know that the
effectiveness of statistical methods does depend on the choice of
solution structure or data model, feature selection, results
interpretation, etc. Today they solve these problems more logically by
applying knowledge, experience and sometimes looking at visual displays
which are often difficult to interpret. Data analysis by pictorial
representation is based on years of research and modeling of human
vision abilities to effectively detect and describe complicated
nonlinear dependencies directly in large dimensional data space.
- January 5, 1994
- Applications of Statistics and Operation Research Methods:Mike
Sweeney, American Greetings Corporation
- Applications of statistics and operations research
methods at American Greetings Corporation will be discussed. A
background on the company will be presented and a description of how
Management Sciences services the needs of the various internal
departments will be provided. Concentration is on solving business
problems through an blend of pure statistics/O.R. and general analytical
methods.
- 1993 Talks
- December 1, 1993 (Cleveland Chapter Presidential Address)
- Comparing the Robustness of Alternative Methods of Exploring
Response Surfaces: Gary Skerl, Glidden Paints
- Traditional methods of response surface analysis
frequently involve fitting a quadratic model to a central composite or
Box-Behnken design. This approach purports to give a reasonable
approximation to the "true" response surface is more complex.
New approaches are emerging which claim to perform better. Two of these
approaches include neural networks and locally weighted regression. A
protocol is proposed for comparing the robustness of these alternative.
An example is given using a simulated test case.
- November 3, 1993
- Optimum Experimental Designs for Comparative Bioavailability