Analysis of longitudinal marginal structural models

Subscribe to email list

Please select the email list(s) to which you wish to subscribe.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Image CAPTCHA

Enter the characters shown in the image.

User menu

You are here

Analysis of longitudinal marginal structural models

TitleAnalysis of longitudinal marginal structural models
Publication TypeJournal Article
Year of Publication2004
AuthorsBryan, J, Yu, Z, Van Der Laan, MJ
JournalBiostatistics
Volume5
Pagination361–380
Date PublishedJul
AbstractIn this article we construct and study estimators of the causal effect of a time-dependent treatment on survival in longitudinal studies. We employ a particular marginal structural model (MSM), proposed by Robins (2000), and follow a general methodology for constructing estimating functions in censored data models. The inverse probability of treatment weighted (IPTW) estimator of Robins et al. (2000) is used as an initial estimator and forms the basis for an improved, one-step estimator that is consistent and asymptotically linear when the treatment mechanism is consistently estimated. We extend these methods to handle informative censoring. The proposed methodology is employed to estimate the causal effect of exercise on mortality in a longitudinal study of seniors in Sonoma County. A simulation study demonstrates the bias of naive estimators in the presence of time-dependent confounders and also shows the efficiency gain of the IPTW estimator, even in the absence such confounding. The efficiency gain of the improved, one-step estimator is demonstrated through simulation.