Hubert / Wainer A Statistical Guide for the Ethically Perplexed

1. Auflage 2012
ISBN: 978-1-4398-7369-4
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 588 Seiten

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.

Zielgruppe

Researchers and graduate students in statistics and social and behavioral sciences.

Autoren/Hrsg.

Hubert, Lawrence

Wainer, Howard

Fachgebiete

• Geisteswissenschaften Philosophie Angewandte Ethik & Soziale Verantwortung
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik

Inhaltsverzeichnis

Preamble

Introduction
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

Correlation
Illusory Correlation
Ecological Correlation
Restriction of Range for Correlations
Odd Correlations
Measures of Nonlinear Association
Intraclass Correlation

Prediction
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
Multivariable Systems
Graphical Presentation
Problems with Multiple Testing
Issues in Repeated-Measures Analyses
Matching and Blocking
Randomization and Permutation Tests
Pitfalls of Software Implementations
Sample Size Selection

Psychometrics
Traditional True Score Theory Concepts of Reliability and Validity
Test Fairness
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

Inferring Causality
Casuistry
The Bradford-Hill Criteria for Determining a Causal Connection
Some Historical Health and Medical Conceptions of Disease Causality
Medical Error as (the) Causative Factor

Simpson’s Paradox

Meta-Analysis

Statistical Sleuthing and Explanation
Sleuthing Interests and Basic Tools
Survival Analysis
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
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
Junk Science
The Consequences of Daubert and the Data Quality Act (of 2001)

Some Concluding Remarks

Bibliography

Author Index
Subject Index

Über Autor(innen)

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.