Analyzing Longitudinal Clinical Trial Data : A Practical Guide (Paperback)

Background and Setting. Introduction. Objectives and estimands?determining what to estimate. Study design?collecting the intended data. Example data. Mixed effects models review. Modeling the observed data. Choice of dependent variable and statistical test. modeling covariance (correlation). Modeling means over time. Accounting for covariates. Categorical data. Model checking and verification. Methods for dealing with missing Data. Overview of missing data. Simple and ad hoc Approaches for dealing with missing data. Direct maximum likelihood. Multiple imputation. Inverse probability. Methods for incomplete categorical data weighted generalized estimated equations. Doubly robust methods. MNAR methods. Methods for incomplete categorical data. A comprehensive approach to study development and analyses. Developing statistical analysis plans. Example analyses of clinical trial data.