title: Analyzing Statistical Mediation with Multiple Informants: A New Approach with an Application in Clinical Psychology.
abstract: Testing mediation models is critical for identifying potential variables that need to be targeted to effectively change one or more outcome variables. In addition, it is now common practice for clinicians to use multiple informant (MI) data in studies of statistical mediation. By coupling the use of MI data with statistical mediation analysis, clinical researchers can combine the benefits of both techniques. Integrating the information from MIs into a statistical mediation model creates various methodological and practical challenges. The authors review prior methodological approaches to MI mediation analysis in clinical research and propose a new latent variable approach that overcomes some limitations of prior approaches. An application of the new approach to mother, father, and child reports of impulsivity, frustration tolerance, and externalizing problems (N = 454) is presented. The results showed that frustration tolerance mediated the relationship between impulsivity and externalizing problems. The new approach allows for a more comprehensive and effective use of MI data when testing mediation models.
authors.affiliation: Department of Psychology, Utah State University, Logan UT, USA.
authors.forename: Lesther A
authors.initials: LA
authors.lastname: Papa
authors.affiliation: Department of Psychology, Utah State University, Logan UT, USA.
authors.forename: Kaylee
authors.initials: K
authors.lastname: Litson
authors.affiliation: Department of Psychology, Utah State University, Logan UT, USA.
authors.forename: Ginger
authors.initials: G
authors.lastname: Lockhart
authors.affiliation: Department of Psychology, Arizona State University, Phoenix AZ, USA.
authors.forename: Laurie
authors.initials: L
authors.lastname: Chassin
authors.affiliation: Department of Psychology, Utah State University, Logan UT, USA.
authors.forename: Christian
authors.initials: C
authors.lastname: Geiser
keywords: indirect effects; multimethod design; multiple informants; multiple raters; statistical mediation