TY - JOUR
T1 - General multivariate linear models for longitudinal studies
AU - Shieh, Gwowen
PY - 2000/12
Y1 - 2000/12
N2 - Longitudinal studies occur frequently in many different disciplines. To fully utilize the potential value of the information contained in a longitudinal data, various multivariate linear models have been proposed. The methodology and analysis are somewhat unique in their own ways and their relationships are not well understood and presented. This article describes a general multivariate linear model for longitudinal data and attempts to provide a constructive formulation of the components in the mean response profile. The objective is to point out the extension and connections of some well-known models that have been obscured by different areas of application. More importantly, the model is expressed in a unified regression form from the subject matter considerations. Such an approach is simpler and more intuitive than other ways to modeling and parameter estimation. As a consequence the analyses of the general class of models for longitudinal data can be easily implemented with standard software.
AB - Longitudinal studies occur frequently in many different disciplines. To fully utilize the potential value of the information contained in a longitudinal data, various multivariate linear models have been proposed. The methodology and analysis are somewhat unique in their own ways and their relationships are not well understood and presented. This article describes a general multivariate linear model for longitudinal data and attempts to provide a constructive formulation of the components in the mean response profile. The objective is to point out the extension and connections of some well-known models that have been obscured by different areas of application. More importantly, the model is expressed in a unified regression form from the subject matter considerations. Such an approach is simpler and more intuitive than other ways to modeling and parameter estimation. As a consequence the analyses of the general class of models for longitudinal data can be easily implemented with standard software.
KW - Doubly multivariate linear models
KW - GMANOVA
KW - Growth curve models
KW - MANOVA
KW - Pooled time series and cross-sectional data
KW - Repeated measures design
KW - Seemingly unrelated regression models
KW - Time-varying covariates
UR - http://www.scopus.com/inward/record.url?scp=26844529423&partnerID=8YFLogxK
U2 - 10.1080/03610920008832512
DO - 10.1080/03610920008832512
M3 - Article
AN - SCOPUS:26844529423
VL - 29
SP - 735
EP - 753
JO - Communications in Statistics Part B: Simulation and Computation
JF - Communications in Statistics Part B: Simulation and Computation
SN - 0361-0918
IS - 4
ER -