Multiple Imputation to Account for Measurement Error in Marginal Structural Models.

ABSTRACT:

Background

Marginal structural models are an important tool for observational studies. These models typically assume that variables are measured without error. We describe a method to account for differential and nondifferential measurement error in a marginal structural model.

Methods

We illustrate the method estimating the joint effects of antiretroviral therapy initiation and current smoking on all-cause mortality in a United States cohort of 12,290 patients with HIV followed for up to 5 years between 1998 and 2011. Smoking status was likely measured with error, but a subset of 3,686 patients who reported smoking status on separate questionnaires composed an internal validation subgroup. We compared a standard joint marginal structural model fit using inverse probability

SUBMITTER: Edwards JK 

PROVIDER: S-EPMC4638124 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature