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Prevention Science

Erschienen in:

01.11.2015

Sample Size for Joint Testing of Indirect Effects

verfasst von: Eric Vittinghoff, Torsten B. Neilands

Erschienen in: Prevention Science | Ausgabe 8/2015

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Abstract

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.

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Titel: Sample Size for Joint Testing of Indirect Effects
verfasst von: Eric Vittinghoff
Torsten B. Neilands
Publikationsdatum: 01.11.2015
Verlag: Springer US
Erschienen in: Prevention Science / Ausgabe 8/2015
Print ISSN: 1389-4986
Elektronische ISSN: 1573-6695
DOI: https://doi.org/10.1007/s11121-014-0528-5

Springer Medizin

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