A Statistical Guide for the Ethically Perplexed
Chapman and Hall/CRC – 2012 – 588 pages
For disciplines concerned with human well-being, such as medicine, psychology, and law, statistics must be used in accordance with standards for ethical practice. A Statistical Guide for the Ethically Perplexed illustrates the proper use of probabilistic and statistical reasoning in the behavioral, social, and biomedical sciences. Designed to be consulted when learning formal statistical techniques, the text describes common instances of both correct and false statistical and probabilistic reasoning.
Lauded for their contributions to statistics, psychology, and psychometrics, the authors make statistical methods relevant to readers’ day-to-day lives by including real historical situations that demonstrate the role of statistics in reasoning and decision making. The historical vignettes encompass the English case of Sally Clark, breast cancer screening, risk and gambling, the Federal Rules of Evidence, "high-stakes" testing, regulatory issues in medicine, difficulties with observational studies, ethics in human experiments, health statistics, and much more. In addition to these topics, seven U.S. Supreme Court decisions reflect the influence of statistical and psychometric reasoning and interpretation/misinterpretation.
Exploring the intersection of ethics and statistics, this comprehensive guide assists readers in becoming critical and ethical consumers and producers of statistical reasoning and analyses. It will help them reason correctly and use statistics in an ethical manner.
"… most should find it of great use as a guide to the literature on aspects of our discipline that we may lack a formal background in. This is especially so if we are most familiar with the application of statistics to the natural sciences rather than the human sciences. I think that a teacher of senior courses in applied statistics would find a use for this book in helping put some real-world flesh on the theoretical bones of the course. It would also be a useful source of readings (or lead to the discovery of readings) for handouts."
—Murray Jorgensen, Australian & New Zealand Journal of Statistics, 2013
"… even the most experienced statisticians will find the extensive quoted extracts and discussions entertaining, informative, and illuminating. … The volume will provide a great source of illustrative material to enliven courses teaching the ideas and methods behind the topics discussed within it. More than that, however, a course, or perhaps a reading group, based around this book would complement the necessarily dryer material describing the ideas and structures of statistical methods. It would drive home the vital importance of statistics to modern society and certainly make the students sit up and take notice.
In short, the authors are to be congratulated on producing a wonderful volume. I believe that all students of statistics, perhaps of science more generally, would benefit substantially from reading it (and then re-reading it when they had a few years’ practical experience under their belts)."
—David J. Hand, International Statistical Review (2013), 81, 2
"… valuable as a reference … . There is a 40-page bibliography, a six-page author index, a 14-page subject index, and a 13-page list of sources, plus a 105 page online supplement that consists mostly of legal decisions and recommended reading. Using all the resources provided, one can assemble a very long list of issues and applications, with readings and references. … recommended … a resource the statistically sophisticated teacher can mine for material from which to create their own examples to engage students."
—Robert W. Hayden, MAA Review, December 2012
"This thorough and readable work covers important topics spanning specific and general causation to experimental design. It offers engaging examples, lucid explanations, and a thorough consideration of truly important issues, giving readers the knowledge to deal more effectively with ethically charged situations. A valuable guide for sorting through ethical issues in the behavioral, social, and biomedical sciences."
—C.K. Gunsalus, Director, National Center for Professional and Research Ethics, and Research Professor, Coordinated Science Laboratory, University of Illinois at Urbana-Champaign
The (Questionable) Use of Statistical Models
TOOLS FROM PROBABILITY AND STATISTICS
Probability Theory: Background and Bayes’ Theorem
The (Mis)assignment of Probabilities
The Probabilistic Generalizations of Logical Fallacies Are No Longer Fallacies
Using Bayes’ Rule to Assess the Consequences of Screening for Rare Events
Bayes’ Rule and the Confusion of Conditional Probabilities
Bayes’ Rule and the Importance of Base Rates
Probability Theory: Application Areas
Some Probability Considerations in Discrimination and Classification
Probability and Litigation
Betting, Gaming, and Risk
Restriction of Range for Correlations
Measures of Nonlinear Association
Regression toward the Mean
Actuarial Versus Clinical Prediction
Incorporating Reliability Corrections in Prediction
Differential Prediction Effects in Selection
Interpreting and Making Inferences from Regression Weights
The (Un)reliability of Clinical Prediction
The Basic Sampling Model and Associated Topics
Problems with Multiple Testing
Issues in Repeated-Measures Analyses
Matching and Blocking
Randomization and Permutation Tests
Pitfalls of Software Implementations
Sample Size Selection
Traditional True Score Theory Concepts of Reliability and Validity
Quotidian Psychometric Insights
Psychometrics, Eugenics, and Immigration Restriction
DATA PRESENTATION AND INTERPRETATION
Background: Data Presentation and Interpretation
Weight-of-the-Evidence Arguments in the Presentation and Interpretation of Data
(Mis)reporting of Data
The Social Construction of Statistics
Adjustments for Groups Not Comparable on a Variable, Such As Age
The Bradford-Hill Criteria for Determining a Causal Connection
Some Historical Health and Medical Conceptions of Disease Causality
Medical Error as (the) Causative Factor
Statistical Sleuthing and Explanation
Sleuthing Interests and Basic Tools
Statistical Sleuthing and the Imposition of the Death Penalty: McCleskey v. Kemp (1987)
EXPERIMENTAL DESIGN AND THE COLLECTION OF DATA
Background: Experimental Design and the Collection of Data
Observational Studies: Interpretation
Observational Studies: Types
Observational Studies: Additional Cautions
Controlled Studies: Additional Sources of Bias
The Randomized Response Method
Ethical Considerations in Data Collection
The Nazi Doctor’s Trial and the Nuremberg Code
The National Research Act of 1974
The Declaration of Helsinki
The Federal Rules of Evidence
The Consequences of Daubert and the Data Quality Act (of 2001)
Some Concluding Remarks
Lawrence Hubert is the Lyle H. Lanier Professor of Psychology and a professor of statistics and educational psychology at the University of Illinois. He is a fellow of the American Statistical Association, American Psychological Association, Association for Psychological Science, American Association for the Advancement of Science, and American Educational Research Association. Dr. Hubert has been a recipient of honors, including the Jacob Cohen Award for Distinguished Contributions to Teaching and Mentoring from Division 5 of the American Psychological Association. His research focuses on the development of exploratory methods for data representation in the behavioral sciences, emphasizing cluster analysis, spatially oriented multidimensional scaling techniques, and network representation procedures.
Howard Wainer is a Distinguished Research Scientist at the National Board of Medical Examiners and adjunct professor of statistics at the Wharton School of the University of Pennsylvania. He is a fellow of the American Statistical Association and American Educational Research Association. Dr. Wainer has been a recipient of several honors, including the Samuel J. Messick Award for Distinguished Scientific Contributions Award from Division 5 of the American Psychological Association and the Career Achievement Award from the National Council on Measurement in Education. His research encompasses the use of graphical methods for data analysis and communication, robust statistical methodology, and the development and application of generalizations of item response theory.