Multiple Overimputation to Address Missing Data and Measurement Error: Application to HIV Treatment During Pregnancy and Pregnancy Outcomes

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Abstract

Background:

Investigations of the association of combination antiretroviral therapy (ART) with pregnancy outcomes often rely on routinely collected clinical data, which are prone to missing data and measurement error. Measurement error in gestational age may bias the relation between combination ART and gestational age-based outcomes.

Methods:

We demonstrate the use of multiple overimputation to address missing data and measurement error in gestational age. Using routinely collected clinical data from public health facilities in Lusaka, Zambia, we multiply imputed missing data and multiply overimputed observed values of gestational age. Poisson models with robust variance estimators were used to estimate risk ratios (RRs) for the associations of duration of combination ART with small for gestational age (SGA) and preterm birth. We compared results from a complete-case analysis, using multiple imputation to address missing data only and using multiple overimputation to address missing data and measurement error.

Results:

In the complete-case analysis, there was no evidence of an association between duration of combination ART and SGA or preterm birth. When we performed multiple overimputation, RRs for SGA moved past the null, but remained imprecise. For preterm birth, RRs for 9–32 weeks of combination ART moved away from the null as the variance due to measurement error increased.

Conclusion:

When we used multiple overimputation to account for measurement error and missing data, we observed an increased risk of preterm birth with longer duration of combination ART. Future analyses examining associations between combination ART and pregnancy outcomes should consider using multiple overimputation to address measurement error in gestational age.

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