Intention-to-treat analyses for incomplete repeated measures data.
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.
Hogan
J W
JW
Center for Statistical Sciences, Brown University, Providence, Rhode Island 02912, USA.
Laird
N M
NM
D000163:Acquired Immunodeficiency Syndrome / Q000188:drug therapy; D000998:Antiviral Agents / Q000008:administration & dosage; D001699:Biometry; D002648:Child; D002985:Clinical Protocols; D003627:Data Interpretation, Statistical; D006801:Humans; D016013:Likelihood Functions; D008137:Longitudinal Studies; D015233:Models, Statistical; D010352:Patient Dropouts; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D013812:Therapeutics; D015215:Zidovudine / Q000008:administration & dosage
D000998:Antiviral Agents; D015215:Zidovudine