Analyzing Factorial Survey Data with Structural Equation Models

Autor/inn/en	Weijters, Bert; Davidov, Eldad; Baumgartner, Hans
Titel	Analyzing Factorial Survey Data with Structural Equation Models
Quelle	In: Sociological Methods & Research, 52 (2023) 4, S.2050-2082 (33 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Weijters, Bert)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0049-1241
DOI	10.1177/00491241211043139
Schlagwörter	Factor Analysis; Structural Equation Models; Regression (Statistics); Social Science Research; Vignettes; Evaluation Methods + Suchen Sie Ihr Suchwort? Faktorenanalyse; Regression; Regressionsanalyse; Social scientific research; Sozialwissenschaftliche Forschung
Abstract	In factorial survey designs, respondents evaluate multiple short descriptions of social objects (vignettes) that experimentally vary different levels of attributes of interest. Analytical methods (including individual-level regression analysis and multilevel models) estimate the weights (or utilities) assigned to the levels of the different attributes by participants to arrive at an overall response to the vignettes. In the current paper, we explain how data from factorial surveys can be analyzed in a structural equation modeling framework using an approach called structural equation modeling for within-subject experiments. We review the use of factorial surveys in social science research, discuss typically used methods to analyze factorial survey data, introduce the structural equation modeling for within-subject experiments approach, and present an empirical illustration of the proposed method. We conclude by describing several extensions, providing some practical recommendations, and discussing potential limitations. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01