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Mediation Modeling in Randomized Trials with Non-normal Outcome Variables

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Biopharmaceutical Applied Statistics Symposium

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Abstract

Mediation analysis seeks to understand the mechanism by which a treatment affects an outcome. Many conventional and causal mediation approaches have been developed for continuous outcomes. When the outcome of interest is non-continuous (e.g., binary, count, or zero-inflated count), mediation approaches relying on linear models may not be appropriate. This chapter introduces the framework and definition of direct and indirect (mediation) treatment effects on non-continuous outcomes around and through intermediate variables (mediators). Different mediation approaches for non-continuous outcomes are discussed under a variety of settings where post-baseline confounders and unmeasured confounders may be a concern, and under a series of assumptions with and without sequential ignorability. Methods are illustrated with application to a randomized dental caries prevention trial.

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Acknowledgements

The authors thank Dean Amid Ismail and Sungwoo Lim for providing the DDHP MI-DVD data which was performed with support from cooperative agreement U54 DE014261. This chapter was made possible by cooperative agreement U54 DE019285 from the National Institute of Dental and Craniofacial Research, a component of the United States National Institutes of Health.

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  1. University of California, San Francisco, USA

    Jing Cheng & Stuart A. Gansky

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  1. Jing Cheng
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Correspondence to Stuart A. Gansky .

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Editors and Affiliations

  1. Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA, USA

    Karl E. Peace

  2. School of Social Work and Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA

    Ding-Geng Chen

  3. Boston University, Cambridge, MA, USA

    Sandeep Menon

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Cheng, J., Gansky, S.A. (2018). Mediation Modeling in Randomized Trials with Non-normal Outcome Variables. In: Peace, K., Chen, DG., Menon, S. (eds) Biopharmaceutical Applied Statistics Symposium . ICSA Book Series in Statistics. Springer, Singapore. https://doi.org/10.1007/978-981-10-7820-0_10

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