A comparison of methods to test mediation and other intervening variable effects.

Abstract

A Monte Carlo study compared 14 methods to test the statistical significance of the intervening variable effect. An intervening variable (mediator) transmits the effect of an independent variable to a dependent variable. The commonly used R. M. Baron and D. A. Kenny (1986) approach has low statistical power. Two methods based on the distribution of the product and 2 difference-incoefficients methods have the most accurate Type I error rates and greatest statistical power except in 1 important case in which Type I error rates are too high. The best balance of Type I error and statistical power across all cases is the test of the joint significance of the two effects comprising the intervening variable effect.The purpose of this article is to compare statistical methods used to test a model in which an independent variable (X) causes an intervening variable (I), which in turn causes the dependent variable (Y). Many different disciplines use such models, with the terminology, assumptions, and statistical tests only partially overlapping among them. In psychology, the X → I → Y relation is often termed mediation (Baron & Kenny, 1986), sociology originally popularized the term indirect effect (Alwin & Hauser, 1975), and in epidemiology, it is termed the surrogate or intermediate endpoint effect (Freedman & Schatzkin, 1992). This article focuses on the statistical performance of each of the available tests of the effect of an intervening variable. Consideration of conceptual issues related to the definition of intervening variable effects is deferred to the final section of the Discussion.Hypotheses articulating measurable processes that intervene between the independent and dependent variables have long been proposed in psychology (e.g., MacCorquodale & Meehl, 1948;Woodworth, 1928). Such hypotheses are fundamental to theory in many areas of basic and applied psychology (Baron & Kenny, 1986;James & Brett, 1984). Reflecting this importance, a search of the Social Science Citation Index turned up more than 2,000 citations of the Baron and Kenny article that presented an important statistical approach to the investigation of these processes. Examples of hypotheses and models that involve intervening variables abound. In basic social psychology, intentions are thought to mediate the relation between attitude and behavior (Ajzen & Fish-bein, 1980). In cognitive psychology, attentional processes are thought to intervene between stimulus and behavior (Stacy, Leigh, & Weingardt, 1994). In industrial psychology, work environment leads to changes in the intervening variable of job perception, which in turn affects behavioral outcomes (James & Brett, 1984 NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript work on preventive health interventions, programs are designed to change proximal variables, which in turn are expected to have beneficial effects on the distal health outcomes of interest (Hansen, 1992; MacKinnon, 1994;West & Aiken, 1997).A search of psychological abstracts from 1996 to 1999 yi...

Mediation in experimental and nonexperimental studies: New procedures and recommendations.

“…The implication of these findings is that the usual test of the indirect effect will lack statistical power to reject the null hypothesis that a × b ‫ס‬ 0. This implication has been documented in computer simulations presented by MacKinnon and his colleagues (see, e.g., MacKinnon et al, 2002). Bollen and Stine (1990) proposed computing nonsymmetric confidence bounds for a × b using bootstrap information.…”

“…Sobel (1982Sobel ( , 1986) derived approximate expressions for that standard error by using a Taylor series approach, and he assumed that the product would tend to be normally distributed as the sample size gets large. Several versions of the approximate standard error have been reported (MacKinnon et al, 1995(MacKinnon et al, , 2002, and two of these versions are most often used in the literature:…”

“…Although statistical analyses of association cannot establish causal links definitively, they can provide evidence that one mediation pattern is more plausible than another, and they can provide invaluable information for the design of fully experimental studies of causal processes (see Bollen, 1989;MacKinnon, Lockwood, Hoffman, West, & Sheets, 2002).…”

Identifying mechanisms that underlie links between COMT genotype and aggression in male adolescents with ADHD

“…Mediation analyses were undertaken according to the criteria proposed by MacKinnon, Lockwood, Hoffman, West, and Sheets (2002). This approach enables statistical tests of the indirect pathway (x ‐> m ‐> y) where the independent variable ( COMT Val158Met genotype; x) and dependent variable (the dimensional measure of aggression symptom score; y) are both significantly associated with the putative mediator (e.g.…”

Racial-Ethnic Disparities in Substance Abuse Treatment: The Role of Criminal History and Socioeconomic Status

“…In addition, we tested the significance of suppressor or mediating effects of six variables (any criminal history, Medicaid enrollment, being uninsured, college graduate, income greater than 400% of the federal poverty level, and being employed) in the fully specified model using the Sobel test (46,47). This test incorporated the association between raceethnicity and the mechanisms of interest as well as the association between the mechanism and substance abuse treatment, conditional on other covariates.…”