Work

Increasing Statistical Power in Mediation Models Without Increasing Sample Size

Year: 2013

Type: article

Abstract: 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.

Source: Evaluation & the Health Professions

DOI: 10.1177/0163278713514250

Authors: Matthew S. Fritz, Matthew G. Cox, David P. MacKinnon

Institutions: University of Nebraska–Lincoln, The University of Texas MD Anderson Cancer Center, Arizona State University

Language: English

Topic: Advanced Causal Inference Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Institute on Drug Abuse