Volume 1: Statistical Methods in
Clinical Studies
Edited by
R. B. D’Agostino,
Boston University, USA
Contents
Preface vii
Preface to Volume 1 ix
Part I OBSERVATIONAL STUDIES/EPIDEMIOLOGY
1.1 Epidemiology
Computing Estimates of Incidence, Including Lifetime Risk: Alzheimer’s Disease in the
Framingham Study. The Practical Incidence Estimators (PIE) Macro. Alexa Beiser,
Ralph B. D’Agostino, Sr, Sudha Seshadri, Lisa M. Sullivan and Philip A. Wolf 3
The Applications of Capture-Recapture Models to Epidemiological Data. Anne Chao,
P. K. Tsay, Sheng-Hsiang Lin, Wen-Yi Shau and Day-Yu Chao 31
1.2 Adjustment Methods
Propensity Score Methods for Bias Reduction in the Comparison of a Treatment to a
Non-Randomized Control Group. Ralph B. D’Agostino, Jr. 67
1.3 Agreement Statistics
Kappa Coecients in Medical Research. Helen Chmura Kraemer,
Vyjeyanthi S. Periyakoil and Art Noda 85
1.4 Survival Models
Survival Analysis in Observational Studies. Kate Bull and David J. Spiegelhalter 107
Methods for Interval-Censored Data. Jane C. Lindsey and Louise M. Ryan 141
Analysis of Binary Outcomes in Longitudinal Studies Using Weighted Estimating
Equations and Discrete-Time Survival Methods: Prevalence and Incidence of
Smoking in an Adolescent Cohort. John B. Carlin, Rory Wolfe, Carolyn Coey
and George C. Patton 161
Part II PROGNOSTIC/CLINICAL PREDICTION MODELS
2.1 Prognostic Variables
Categorizing a Prognostic Variable: Review of Methods, Code for Easy Implementation
and Applications to Decision-Making about Cancer Treatments. Madhu Mazumdar
and Jill R. Glassman 189
v
vi CONTENTS
2.2 Prognostic/Clinical Prediction Models
Development of Health Risk Appraisal Functions in the Presence of Multiple Indicators:
The Framingham Study Nursing Home Institutionalization Model. R. B. D’Agostino,
Albert J. Belanger, Elizabeth W. Markson, Maggie Kelly-Hayes and Philip A. Wolf 209
Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions
and Adequacy, and Measuring and Reducing Errors. Frank E. Harrell Jr.,
Kerry L. Lee and Daniel B. Mark 223
Development of a Clinical Prediction Model for an Ordinal Outcome: The World
Health Organization Multicentre Study of Clinical Signs and Etiological Agents of
Pneumonia, Sepsis and Meningitis in Young Infants. Frank E. Harrell Jr.,
Peter A. Margolis, Sandy Gove, Karen E. Mason, E. Kim Mulholland,
Deborah Lehmann, Lulu Muhe, Salvacion Gatchalian, Heinz F. Eichenwald and
the WHO/ARI Young Infant Multicentre Study Group 251
Using Observational Data to Estimate Prognosis: An Example Using a Coronary Artery
Disease Registry. Elizabeth R. DeLong, Charlotte L. Nelson, John B. Wong,
David B. Pryor, Eric D. Peterson, Kerry L. Lee, Daniel B. Mark,
Robert M. Cali and Stephen G. Pauker 287
Part III CLINICAL TRIALS
3.1 Design
Designing Studies for Dose Response. Weng Kee Wong and Peter A. Lachenbruch 317
3.2 Monitoring
Bayesian Data Monitoring in Clinical Trials. Peter M. Fayers, Deborah Ashby and
Mahesh K. B. Parmar 335
3.3 Analysis
Longitudinal Data Analysis (Repeated Measures) in Clinical Trials. Paul S. Albert 353
Repeated Measures in Clinical Trials: Simple Strategies for Analysis Using Summary
Measures. Stephen Senn, Lynda Stevens and Nish Chaturvedi 379
Strategies for Comparing Treatments on a Binary Response with Multi-Centre Data.
Alan Agresti and Jonathan Hartzel 397
A Review of Tests for Detecting a Monotone Dose-Response Relationship with
Ordinal Response Data. Christy Chuang-Stein and Alan Agresti 423
Index 443