Analyzing Statistical Mediation with Multiple Informants: A New Approach with an Application in Clinical Psychology

Frontiers in Psychology

Laurie eChassin¹  Ginger eLockhart¹  Christian eGeiser¹  Lesther ePapa¹  Kaylee eLitson¹ 

[1] Utah State University;

关键词: statistical mediation;    multiple raters;    Indirect effects;    Multiple informants;    Multimethod design;   

DOI  :  10.3389/fpsyg.2015.01674

来源: DOAJ

【 摘 要 】

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. Advantages and limitations of the new approach are discussed. The new approach can help clinical researchers overcome limitations of prior techniques. It allows for a more comprehensive and effective use of MI data when testing mediation models.

【 授权许可】

Unknown