On the Importance of Reliable Covariate Measurement in Selection Bias Adjustments Using Propensity Scores

Autor/inn/en	Steiner, Peter M.; Cook, Thomas D.; Shadish, William R.
Titel	On the Importance of Reliable Covariate Measurement in Selection Bias Adjustments Using Propensity Scores
Quelle	In: Journal of Educational and Behavioral Statistics, 36 (2011) 2, S.213-236 (24 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998610375835
Schlagwörter	Statistical Bias; Reliability; Measurement; Scores; Error of Measurement; Undergraduate Students + Suchen Sie Ihr Suchwort? Reliabilität; Messverfahren; Messfehler
Abstract	The effect of unreliability of measurement on propensity score (PS) adjusted treatment effects has not been previously studied. The authors report on a study simulating different degrees of unreliability in the multiple covariates that were used to estimate the PS. The simulation uses the same data as two prior studies. Shadish, Clark, and Steiner showed that a PS formed from many covariates demonstrably reduced selection bias, while Steiner, Cook, Shadish, and Clark identified the subsets of covariates from the larger set that were most effective for bias reduction. Adding different degrees of random error to these covariates in a simulation, the authors demonstrate that unreliability of measurement can degrade the ability of PSs to reduce bias. Specifically, increases in reliability only promote bias reduction, if the covariates are effective in reducing bias to begin with. Increasing or decreasing the reliability of covariates that do not effectively reduce selection bias makes no difference at all. (Contains 5 figures, 3 tables and 6 notes.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10