Handbook of Statistical Methods for Case-Control Studies is written by leading researchers in the field. It provides an in-depth treatment of up-to-date and currently developing statistical methods for the design and analysis of case-control studies, as well as a review of classical principles and methods. The handbook is designed to serve as a reference text for biostatisticians and quantitatively-oriented epidemiologists who are working on the design and analysis of case-control studies or on related statistical methods research. Though not specifically intended as a textbook, it may also be used as a backup reference text for graduate level courses.
- Classical designs and causal inference, measurement error, power, and small-sample inference
- Designs that use full-cohort information
- Time-to-event data
- Genetic epidemiology
Introduction. Introduction. Origins. Classical Case-Control Studies. Design issues in case-control studies. Basic concepts and methods of analysis. Matched samples. Beyond logistic regression. Small sample methods. Multiple case or control groups. Power and sample size. Causal inference. Misclassification and measurement error. Analysis of secondary phenotype under case-control design. Sampling from a Defined Cohort. Two and three (or multi) phase sampling designs. Calibration and estimation of sampling weights. Maximum likelihood. Re-use of case-control samples. Misspecification. Case-control studies with complex sampling. Cohort sampling for time to event data. Case-cohort designs and analyses. Design options and partial likelihood analyses of nested case-control data. Inverse probability weighting in nested case-control studies. Multiple imputation. Maximum likelihood. Self controlled case series. Genetic Epidemiology. Basic design and association analysis of population-based case-control studies. Analysis of gene-environment interactions. Screening methods for detecting genetic association and interactions under case-control design. Analysis of family-based case-control studies. Fitting mixed model to case-control genome-wide association studies. Analysis of secondary phenotype under case-control design.