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.
National Institute for Agro-Environmental Sciences, Tsukuba, Japan. yamamura@affrc.go.jp
Kohji
K
Yamamura
D000818:Animals; D005163:Factor Analysis, Statistical; D006801:Humans; D008137:Longitudinal Studies; D017711:Nonlinear Dynamics; D013997:Time Factors