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Epidemiology. 2015 Sep;26(5):645-52. doi: 10.1097/EDE.0000000000000330.

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

Author information

1
From the aDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC; bDivision of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA; cDivision of Infectious Diseases, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC; dSchool of Medicine, University of California, San Diego, San Diego, CA; eSchool of Medicine, Johns Hopkins University, Baltimore, MD; fFenway Health, Boston, MA; and gDivision of Infectious Diseases, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL.

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 weights to a model that also accounted for misclassification of smoking status using multiple imputation.

RESULTS:

In the standard analysis, current smoking was not associated with increased risk of mortality. After accounting for misclassification, current smoking without therapy was associated with increased mortality (hazard ratio [HR]: 1.2 [95% confidence interval [CI] = 0.6, 2.3]). The HR for current smoking and therapy [0.4 (95% CI = 0.2, 0.7)] was similar to the HR for no smoking and therapy (0.4; 95% CI = 0.2, 0.6).

CONCLUSIONS:

Multiple imputation can be used to account for measurement error in concert with methods for causal inference to strengthen results from observational studies.

PMID:
26214338
PMCID:
PMC4638124
DOI:
10.1097/EDE.0000000000000330
[Indexed for MEDLINE]
Free PMC Article

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