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Sensitivity analysis for unobserved confounding in causal mediation analysis allowing for effect modification, censoring and truncation

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  • Anita Lindmark

    (Umeå University)

Abstract

Causal mediation analysis is used to decompose the total effect of an exposure on an outcome into an indirect effect, taking the path through an intermediate variable, and a direct effect. To estimate these effects, strong assumptions are made about unconfoundedness of the relationships between the exposure, mediator and outcome. These assumptions are difficult to verify in a given situation and therefore a mediation analysis should be complemented with a sensitivity analysis to assess the possible impact of violations. In this paper we present a method for sensitivity analysis to not only unobserved mediator-outcome confounding, which has largely been the focus of previous literature, but also unobserved confounding involving the exposure. The setting is estimation of natural direct and indirect effects based on parametric regression models. We present results for combinations of binary and continuous mediators and outcomes and extend the sensitivity analysis for mediator-outcome confounding to cases where the continuous outcome variable is censored or truncated. The proposed methods perform well also in the presence of interactions between the exposure, mediator and observed confounders, allowing for modeling flexibility as well as exploration of effect modification. The performance of the method is illustrated through simulations and an empirical example.

Suggested Citation

  • Anita Lindmark, 2022. "Sensitivity analysis for unobserved confounding in causal mediation analysis allowing for effect modification, censoring and truncation," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 785-814, October.
    • Handle: RePEc:spr:stmapp:v:31:y:2022:i:4:d:10.1007_s10260-021-00611-4
    DOI: 10.1007/s10260-021-00611-4
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    1. Hausman, Jerry A & Wise, David A, 1977. "Social Experimentation, Truncated Distributions, and Efficient Estimation," Econometrica, Econometric Society, vol. 45(4), pages 919-938, May.
    2. Powell, James L, 1986. "Symmetrically Trimmed Least Squares Estimation for Tobit Models," Econometrica, Econometric Society, vol. 54(6), pages 1435-1460, November.
    3. Martin Huber, 2014. "Identifying Causal Mechanisms (Primarily) Based On Inverse Probability Weighting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(6), pages 920-943, September.
    4. Lee, Myoung-jae, 1993. "Quadratic mode regression," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 1-19.
    5. Steen, Johan & Loeys, Tom & Moerkerke, Beatrijs & Vansteelandt, Stijn, 2017. "medflex: An R Package for Flexible Mediation Analysis using Natural Effect Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i11).
    6. Vijverberg, Wim P M, 1987. "Non-normality as Distributional Misspecification in Single-Equation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 49(4), pages 417-430, November.
    7. Minna Genbäck & Nawi Ng & Elena Stanghellini & Xavier de Luna, 2018. "Predictors of decline in self-reported health: addressing non-ignorable dropout in longitudinal studies of aging," European Journal of Ageing, Springer, vol. 15(2), pages 211-220, June.
    8. Minna Genbäck & Elena Stanghellini & Xavier Luna, 2015. "Uncertainty intervals for regression parameters with non-ignorable missingness in the outcome," Statistical Papers, Springer, vol. 56(3), pages 829-847, August.
    9. Arne Henningsen & Ott Toomet, 2011. "maxLik: A package for maximum likelihood estimation in R," Computational Statistics, Springer, vol. 26(3), pages 443-458, September.
    10. Tingley, Dustin & Yamamoto, Teppei & Hirose, Kentaro & Keele, Luke & Imai, Kosuke, 2014. "mediation: R Package for Causal Mediation Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 59(i05).
    11. Laitila, Thomas, 2001. "Properties of the QME under asymmetrically distributed disturbances," Statistics & Probability Letters, Elsevier, vol. 52(4), pages 347-352, May.
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