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Intention-to-Treat Analyses for Incomplete Repeated Measures Data
Joseph W. Hogan and Nan M. Laird
Vol. 52, No. 3 (Sep., 1996), pp. 1002-1017
Published by: International Biometric Society
Stable URL: http://www.jstor.org/stable/2533061
Page Count: 16
You can always find the topics here!Topics: School dropouts, Censorship, Statistical estimation, Biometrics, Clinical trials, Modeling, Statistical models, Statistical variance, Standard error, Missing data
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In a randomized longitudinal clinical trial designed to evaluate two or more rival treatments, an intent-to-treat analysis requires inclusion of all randomized patients, regardless of whether they remain on protocol for the duration of the study. We propose a piecewise linear random effects model for analyzing longitudinal data where the multivariate outcome can depend upon time spent on treatment. The model assumes that data are available on a random sample of subjects after treatment is terminated, and allows either a pragmatic or explanatory analysis (as defined by Schwartz and Lellouch, 1967, Journal of Chronic Diseases 20, 637-648). Full maximum likelihood estimation of the model parameters is carried out using widely available statistical software for repeated measures with missing data and for nonparametric survival curve estimation. Data from a national, multicenter pediatric AIDS clinical trial are analyzed to illustrate implementation and interpretation of the model.
Biometrics © 1996 International Biometric Society