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Random effects logistic models for analysing efficacy of a longitudinal randomized treatment with non‐adherence
Author(s) -
Small Dylan S.,
Ten Have Thomas R.,
Joffe Marshall M.,
Cheng Jing
Publication year - 2005
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.2313
Subject(s) - logistic regression , randomized controlled trial , random effects model , statistics , econometrics , medicine , mathematics , meta analysis
Abstract We present a random effects logistic approach for estimating the efficacy of treatment for compliers in a randomized trial with treatment non‐adherence and longitudinal binary outcomes. We use our approach to analyse a primary care depression intervention trial. The use of a random effects model to estimate efficacy supplements intent‐to‐treat longitudinal analyses based on random effects logistic models that are commonly used in primary care depression research. Our estimation approach is an extension of Nagelkerke et al. 's instrumental variables approximation for cross‐sectional binary outcomes. Our approach is easily implementable with standard random effects logistic regression software. We show through a simulation study that our approach provides reasonably accurate inferences for the setting of the depression trial under model assumptions. We also evaluate the sensitivity of our approach to model assumptions for the depression trial. Copyright © 2005 John Wiley & Sons, Ltd.