Statistical considerations in identifying mechanisms of change.
The statistical search for mechanisms of change involves multiple inferential tests, ones that generally follow a fixed sequence designed to demonstrate mediation. While there are several popular approaches to conducting such tests, e.g., SEM and MRA, the inflated Type I error rate problem associated with conducting these tests has received little, if any, attention. This paper offers 2 solutions to avoid committing Type I errors associated with mediational tests. Most straightforward, investigators may choose to use a Bonferroni adjustment. In contrast, a design-based approach can be used that tests rival explanations for the observed effects. Examples drawn from addiction research are provided.
Tonigan
J Scott
JS
Center on Alcoholism, Substance Abuse and Addictions, Department of Psychology, University of New Mexico, Albuquerque, NM 87131, USA. jtonigan@unm.edu
D000437:Alcoholism / Q000523:psychology / Q000628:therapy*; D006801:Humans; D010043:Outcome and Process Assessment, Health Care / Q000379:methods*; D013223:Statistics as Topic / Q000379:methods*