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Assessing the effectiveness of antiretroviral adherence interventions. Using marginal structural models to replicate the findings of randomized controlled trials.

Authors
  • Petersen, Maya L
  • Wang, Yue
  • van der Laan, Mark J
  • Bangsberg, David R
Type
Published Article
Journal
JAIDS Journal of Acquired Immune Deficiency Syndromes
Publisher
Ovid Technologies (Wolters Kluwer) - Lippincott Williams & Wilkins
Publication Date
Dec 01, 2006
Volume
43 Suppl 1
Identifiers
PMID: 17133209
Source
Medline
License
Unknown

Abstract

Randomized controlled trials of interventions to improve adherence to antiretroviral medications are not always feasible. Marginal structural models (MSM) are a statistical methodology that aims to replicate the findings of randomized controlled trials using observational data. Under the assumption of no unmeasured confounders, 3 MSM estimators are available to estimate the causal effect of an intervention. Two of these estimators, G-computation and inverse probability of treatment weighted (IPTW), can be implemented using standard software. G-computation relies on fitting a multivariable regression of adherence on the intervention and confounders. Thus, it is related to the standard multivariable regression approach to estimating causal effects. In contrast, IPTW relies on fitting a multivariable logistic regression of the intervention on confounders. This article reviews the implementation of these methods, the assumptions underlying them, and interpretation of results. Findings are illustrated with a theoretic data example in which MSM are used to estimate the effect of a behavioral intervention on adherence to antiretroviral therapy.

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