Psychometric Models for Scoring Multiple Reporter Assessments: Applications to Integrative Data Analysis in Prevention Science and Beyond

Autor/inn/en	Curran, Patrick J.; Georgeson, A. R.; Bauer, Daniel J.; Hussong, Andrea M.
Titel	Psychometric Models for Scoring Multiple Reporter Assessments: Applications to Integrative Data Analysis in Prevention Science and Beyond
Quelle	In: International Journal of Behavioral Development, 45 (2021) 1, S.40-50 (11 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Curran, Patrick J.) ORCID (Georgeson, A. R.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0165-0254
DOI	10.1177/0165025419896620
Schlagwörter	Psychometrics; Scoring; Prevention; Scores; Barriers; Scientific Research; Data Analysis; Validity; Reliability; Outcomes of Treatment; Simulation + Suchen Sie Ihr Suchwort? Psychometry; Psychometrie; Bewertung; Prävention; Vorbeugung; Auswertung; Gültigkeit; Reliabilität; Simulation program; Simulationsprogramm
Abstract	Conducting valid and reliable empirical research in the prevention sciences is an inherently difficult and challenging task. Chief among these is the need to obtain numerical scores of underlying theoretical constructs for use in subsequent analysis. This challenge is further exacerbated by the increasingly common need to consider multiple reporter assessments, particularly when using integrative data analysis to fit models to data that have been pooled across two or more independent samples. The current article uses both simulated and real data to examine the utility of a recently proposed psychometric model for multiple reporter data called the trifactor model (TFM) in settings that might be commonly found in prevention research. Results suggest that numerical scores obtained using the TFM are superior to more traditional methods, particularly when pooling samples that contribute different reporter perspectives. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01