title: Sample Size for Joint Testing of Indirect Effects.
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.
authors.affiliation: Department of Epidemiology and Biostatistics, University of California San Francisco, 550 16th Street, 2nd Floor, San Francisco, CA, 94158, USA. eric.vittinghoff@ucsf.edu.
authors.forename: Eric
authors.initials: E
authors.lastname: Vittinghoff
authors.affiliation: Department of Medicine, Center for AIDS Prevention Studies, University of California San Francisco, 550 16th Street, 3rd Floor, San Francisco, CA, 94158, USA.
authors.forename: Torsten B
authors.initials: TB
authors.lastname: Neilands
mesh_terms: D015233:Models, Statistical; D016012:Poisson Distribution; D012107:Research Design; D018401:Sample Size
keywords: Generalized linear models.; Indirect pathway; Mediation; Power; Sample size