Abstract
AbstractDirect effects in mediation analysis quantify the effect of an exposure on an outcome not mediated by a certain intermediate. When estimating direct effects through measured data, misclassification may occur in the outcomes, exposures, and mediators. In mediation analysis, any such misclassification may lead to biased estimates in the direct effects. Basing on the conditional dependence between the mismeasured variable and other variables given the true variable, misclassification mechanisms can be divided into non-differential misclassification and differential misclassification. In this article, several scenarios of differential misclassification will be discussed and sensitivity analysis results on direct effects will be derived for those eligible scenarios. According to our findings, the estimated direct effects are not necessarily biased in intuitively predictable directions when the misclassification is differential. The bounds of the true effects are functions of measured effects and sensitivity parameters. An example from the 2018 NCHS data will illustrate how to conduct sensitivity analyses with our results on misclassified outcomes, gestational hypertension and eclampsia, when the exposure is Hispanic women versus non-Hispanic White women and the mediator is weights gain during pregnancy.
Highlights
Measurement error is one of the central threats to validity in observational studies [1,2,3,4,5,6,7,8,9,10,11]
We focus on sensitivity analysis for measurement error in the context of mediation analysis of binary variables
We provide sensitivity analysis results for controlled direct effect and natural direct effect in mediation analysis
Summary
Measurement error is one of the central threats to validity in observational studies [1,2,3,4,5,6,7,8,9,10,11]. Among the previous work, [12] conclude that a non-differential misclassified binary outcome biases the estimators of controlled direct effect, natural direct effect, and natural indirect effect on the risk difference scale towards the null. [13] conclude that ignoring non-differential misclassification in exposure increases type I error in mediation analysis. [14] consider non-differential misclassification in a binary mediator and conclude that the natural direct effect on the risk difference scale is overestimated. A recent work [11] considers the impact of differential misclassification in outcome or exposure on causal effect on risk ratio estimates. We extend the work in [11] to provide sensitivity analysis results for controlled direct effect and natural direct effect on the risk/odds ratio scale. Following the discussion in [17], we consider the situation where misclassification of gestational hypertension and eclampsia may be differential and depend on ethnicity
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