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.
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