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Marginal Regression for Binary Longitudinal Data in Adaptive Clinical Trials
Author(s) -
SUTRADHAR BRAJENDRA C.,
BISWAS ATANU,
BARI WASIMUL
Publication year - 2005
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/j.1467-9469.2005.00417.x
Subject(s) - mathematics , statistics , longitudinal data , regression , binary data , marginal model , binary number , regression analysis , econometrics , data mining , computer science , arithmetic
. In an adaptive clinical trial research, it is common to use certain data‐dependent design weights to assign individuals to treatments so that more study subjects are assigned to the better treatment. These design weights must also be used for consistent estimation of the treatment effects as well as the effects of the other prognostic factors. In practice, there are however situations where it may be necessary to collect binary responses repeatedly from an individual over a period of time and to obtain consistent estimates for the treatment effect as well as the effects of the other covariates in such a binary longitudinal set up. In this paper, we introduce a binary response‐based longitudinal adaptive design for the allocation of individuals to a better treatment and propose a weighted generalized quasi‐likelihood approach for the consistent and efficient estimation of the regression parameters including the treatment effects.