Sample Size for Joint Testing of Indirect Effects
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This paper presents methods to calculate sample size for evaluating mediation by joint testing of both links in an indirect pathway from exposure to mediator to outcome. Calculations rely on simulations of the underlying data structure, with testing of the two links performed under the simplifying assumption that the two test statistics are asymptotically independent. Simulations show that the proposed methods are accurate. Continuous and binary exposures and mediators, as well as continuous, binary, count, and survival outcomes are accommodated, along with over-dispersion of count outcomes, design effects, and confounding of the exposure-mediator and mediator-outcome relationships. An illustrative example is provided, and a documented R program implementing the calculations is available online.
KeywordsMediation Indirect pathway Sample size Power Generalized linear models.
The work of Torsten B. Neilands on this research was supported by National Institutes of Health Grant P30 MH062246. The authors thank Charles E. McCulloch and Steven Gregorich for helpful discussions.
Conflict of interests
The authors declare that they have no conflict of interest.
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