Volume 182, Issue 4
Original Article

Multisite causal mediation analysis in the presence of complex sample and survey designs and non‐random non‐response

Xu Qin

Corresponding Author

E-mail address: xuqin@pitt.edu

University of Pittsburgh, USA

Address for correspondence: Xu Qin, Department of Psychology in Education, University of Pittsburgh, 144 North Dithridge Street, 510 Pittsburgh, PA 15213, USA. E-mail: E-mail address: xuqin@pitt.eduSearch for more papers by this author
Jonah Deutsch

Mathematica Policy Research, Chicago, USA

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Edward Bein

Food and Drug Administration, Silver Spring, USA

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First published: 14 April 2019
Citations: 1

Summary

This study provides a template for multisite causal mediation analysis using a comprehensive weighting‐based analytic procedure that enhances external and internal validity. The template incorporates a sample weight to adjust for complex sample and survey designs, adopts an inverse probability of treatment weight to adjust for differential treatment assignment probabilities, employs an estimated non‐response weight to account for non‐random non‐response and utilizes a propensity‐score‐based weighting strategy to decompose flexibly not only the population average but also the between‐site heterogeneity of the total programme impact. Because the identification assumptions are not always warranted, a weighting‐based balance checking procedure assesses the remaining overt bias, whereas a weighting‐based sensitivity analysis further evaluates the potential bias related to omitted confounding or to propensity score model misspecification. We derive the asymptotic variance of the estimators for the causal effects that account for the sampling uncertainty in the estimated weights. The method is applied to a reanalysis of the data from the National Job Corps Study.

Number of times cited according to CrossRef: 1

  • Randomized Experiments in Education, with Implications for Multilevel Causal Inference, Annual Review of Statistics and Its Application, 10.1146/annurev-statistics-031219-041205, 7, 1, (177-208), (2020).