Analyzing Longitudinal Clinical Trial Data: A Practical Guide
provides practical and easy to implement approaches for bringing the
latest theory on analysis of longitudinal clinical trial data into
routine practice.The book, with its example-oriented approach that
includes numerous SAS and R code fragments, is an essential resource for
statisticians and graduate students specializing in medical research.
The authors provide clear descriptions of the relevant statistical
theory and illustrate practical considerations for modeling longitudinal
data. Topics covered include choice of endpoint and statistical test;
modeling means and the correlations between repeated measurements;
accounting for covariates; modeling categorical data; model
verification; methods for incomplete (missing) data that includes the
latest developments in sensitivity analyses, along with approaches for
and issues in choosing estimands; and means for preventing missing data.
Each chapter stands alone in its coverage of a topic. The concluding
chapters provide detailed advice on how to integrate these independent
topics into an over-arching study development process and statistical
analysis plan.