@inbook{cb224de80dca4ec69afe394d4cc6a066,
title = "14 Statistical Modeling in Biomedical Research: Longitudinal Data Analysis",
abstract = "This chapter discusses some major statistical methods for longitudinal data analysis in biomedical research. We have provided a detailed review to some of the most used statistical models for the analyses of longitudinal data and relevant design issues based on these models. Our focus is on the conceptualization of longitudinal statistical models, the assumptions associated with them, and the interpretations of model parameters. It is not our intention to present the detailed theory on statistical estimations and inferences for these models in this chapter. Instead, we have presented the implementations for some of these basic longitudinal models in SAS through real-world applications.",
author = "Chengjie Xiong and Kejun Zhu and Kai Yu and Miller, {J. Philip}",
note = "Funding Information: The work was supported by National Institute on Aging grants AG 03991 and AG 05681 (for C.X. and J.P.M.) and AG 025189 (for C.X.). The work of K.Z. was supported by the National Natural Science Foundation, Grant # 70275101, of People's Republic of China.",
year = "2007",
doi = "10.1016/S0169-7161(07)27014-2",
language = "English",
isbn = "9780444528018",
series = "Handbook of Statistics",
pages = "429--463",
editor = "C.R. Rao and J.P. Miller and D.C. Rao",
booktitle = "Epidemiology and Medical Statistics",
}