Why Are Mediation Effects so Small?

Autor/in	Walters, Glenn D.
Titel	Why Are Mediation Effects so Small?
Quelle	In: International Journal of Social Research Methodology, 22 (2019) 2, S.219-232 (14 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Walters, Glenn D.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1364-5579
DOI	10.1080/13645579.2018.1517232
Schlagwörter	Effect Size; Statistical Analysis; Sampling; Statistical Inference; Computation; Predictor Variables; Error of Measurement; Adolescents; Bullying; Conceptual Tempo; Substance Abuse; Illinois + Suchen Sie Ihr Suchwort? Statistische Analyse; Inferential statistics; Schließende Statistik; Prädiktor; Messfehler; Adolescent; Adolescence; Adoleszenz; Jugend; Jugendalter; Jugendlicher; Mobbing; Drug use; Drug consomption; Drogenkonsum
Abstract	Identifying mediators in variable chains as part of a causal mediation analysis can shed light on issues of causation, assessment, and intervention. However, coefficients and effect sizes in a causal mediation analysis are nearly always small. This can lead those less familiar with the approach to reject the results of causal mediation analysis. The current paper highlights five factors that contribute to small path coefficients in mediation research: loss of information when measuring relationships across time, controlling for prior levels of a predicted variable, adding control variables to the analysis, ignoring measurement error in one's variables, and using multiple mediators. It is argued that these issues are best handled by increasing the statistical power of the analysis, identifying the optimal temporal interval between variables, using bootstrapped confidence intervals to analyze the results, and finding alternate ways of assessing the meaningfulness of the indirect effect. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01