Increasing Statistical Power in Mediation Models Without Increasing Sample Size

Inadequate statistical power to detect treatment effects in health research is a problem that is compounded when testing for mediation. In general, the preferred strategy for increasing power is to increase the sample size, but there are many situations where additional participants cannot be recrui...

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Bibliographic Details
Published in:Evaluation & the health professions 2015-09, Vol.38 (3), p.343-366
Main Authors: Fritz, Matthew S., Cox, Matthew G., MacKinnon, David P.
Format: Article
Language:English
Subjects:
Health administration
Health Services Research
Health technology assessment
Humans
Models, Statistical
Regression analysis
Research Design
Sample Size
Simulation
Statistics
Variables
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Summary:Inadequate statistical power to detect treatment effects in health research is a problem that is compounded when testing for mediation. In general, the preferred strategy for increasing power is to increase the sample size, but there are many situations where additional participants cannot be recruited, necessitating the use of other methods to increase statistical power. Many of these other strategies, commonly applied to analysis of variance and multiple regression models, can be applied to mediation models with similar results. Additional predictors or blocking variables will increase or decrease statistical power, however, depending on whether these variables are related to the mediator, the outcome, or both. The effect of these two methods on the power for tests of mediation is illustrated through the use of simulations. Implications for health researchers using these methods are discussed.
ISSN:0163-2787
1552-3918
DOI:10.1177/0163278713514250