Extended key-factor/key-stage analysis for longitudinal data.

Key-factor/key-stage analysis was originally a descriptive approach to analyze life tables. However, this method can be extended to analyze longitudinal data in pharmaceutical experiments. By dividing the variance into components, the extended key-factor/key-stage analysis indicates which factor is influential, and through which stage the factor generates its influence in determining the outcome of treatments. Such knowledge helps us in constructing a class of nonlinear longitudinal models that can be interpretable than linear models. Example SAS programs and R programs are provided for the calculation. Supplemental materials are available for this article. Go to the publisher's online edition of Journal of Biopharmaceutical Statistics to view the supplemental files.