Causal Indicators Can Help to Interpret Factors

Autor/in	Bentler, Peter M.
Titel	Causal Indicators Can Help to Interpret Factors
Quelle	In: Measurement: Interdisciplinary Research and Perspectives, 14 (2016) 3, S.98-100 (3 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1536-6367
DOI	10.1080/15366367.2016.1224964
Schlagwörter	Stellungnahme; Causal Models; Factor Analysis; Prediction; Scores; Equations (Mathematics); Data Interpretation + Suchen Sie Ihr Suchwort? Kausalanalyse; Faktorenanalyse; Vorhersage; Equations; Mathematics; Gleichungslehre; Data evaluation; Datenauswertung
Abstract	The latent factor in a causal indicator model is no more than the latent factor of the factor part of the model. However, if the causal indicator variables are well-understood and help to improve the prediction of individuals' factor scores, they can help to interpret the meaning of the latent factor. Aguirre-Urreta, Rönkkö, and Marakas (2016) have provided an important theoretical discussion as well as empirical demonstration that in so-called causal indicator models, the meaning or interpretation of the latent variable should be based on the variables that define the common factor and not on the variables that predict the common factor. Figure 2 of Aguirre-Urreta et al., a mimic model, illustrates the point well. In this model, exogenous variables x[subscript 1] and x[subscript 2] imperfectly predict a latent factor ? that in turn predicts endogenous variables y[subscript 1] and y[subscript 2], and the issue at hand is whether the meaning of ? is derived from the x or the y variables. They conclude that although the x variables may help to identify the model, the latent factor ? must be interpreted via the endogenous y[subscript 1] and y[subscript 2] variables and not via the exogenous x[subscript 1] and x[subscript 2] variables. In this article, the author argues that such a model can help improve one's understanding of what a latent variable might actually be; that is, it may shed light on the meaning or interpretation of a latent variable. (ERIC).
Anmerkungen	Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01