Analysis of repeated measurement data is a recurrent challenge to statisticians engaged in biological and biomedical applications. For example, data from clinical trials are often longitudinal in nature, with repeated measures of response taken over time. In pharmacokinetic studies, serial measurements of drug concentrations are taken from each participant. By definition, growth studies involve repeated measurements over time. In other applications, measurements on experimental units may be repeated across some other dimension, e.g. spatially rather than temporally.

Thisvolumecontains Raymond J.Carroll'sresearch and commentary on its impactby leading statisticians. Each of theseven main partsfocuseson a key researcharea: Measurement Error, Transformation and Weighting, Epidemiology, Nonparametric and Semiparametric Regression for Independent Data, Nonparametric and Semiparametric Regression for Dependent Data, Robustness, and other work. The seven subject areas reviewedin this book were chosen by Ray himself, as were the articles representing eacharea. The commentaries not only review Ray's work, but are alsofilled with historyand anecdotes. Raymond J....

Thisvolumecontains Raymond J.Carroll'sresearch and commentary on its impactby leading statisticians. Each of theseven main partsfocuseson a key researcharea: Measurement Error, Transformation and Weighting, Epidemiology, Nonparametric and Semiparametric Regression for Independent Data, Nonparametric and Semiparametric Regression for Dependent Data, Robustness, and other work. The seven subject areas reviewedin this book were chosen by Ray himself, as were the articles representing eacharea. The commentaries not only review Ray s work, but are alsofilled with historyand anecdotes. Raymond J....