Propensity Score Analysis with Fallible Covariates: A Note on a Latent Variable Modeling Approach

Autor/in	Raykov, Tenko
Titel	Propensity Score Analysis with Fallible Covariates: A Note on a Latent Variable Modeling Approach
Quelle	In: Educational and Psychological Measurement, 72 (2012) 5, S.715-733 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164412440999
Schlagwörter	Computation; Probability; Error of Measurement; Observation; Models; Statistical Analysis + Suchen Sie Ihr Suchwort? Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Messfehler; Beobachtung; Analogiemodell; Statistische Analyse
Abstract	A latent variable modeling approach that permits estimation of propensity scores in observational studies containing fallible independent variables is outlined, with subsequent examination of treatment effect. When at least one covariate is measured with error, it is indicated that the conventional propensity score need not possess the desirable property of bias adjustment with respect to possible prior group differences. For this setting, a modified propensity score is discussed that is based on true scores on fallible covariates and perfectly measured covariates, if available. This modified score can be recommended to use for average treatment effect evaluation in circumstances where selection into groups occurs on corresponding underlying latent dimensions measured with error. The proposed propensity score procedure is illustrated with an example. (Contains 3 notes and 4 tables.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10