A Promising New Approach to Eliminating Selection Bias

Autor/inn/en	Peck, Laura R.; Camillo, Furio; D'Attoma, Ida
Titel	A Promising New Approach to Eliminating Selection Bias
Quelle	In: Canadian Journal of Program Evaluation, 24 (2009) 2, S.31-56 (26 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0834-1516
Schlagwörter	Program Evaluation; Intervention; Experiments; Comparative Analysis; Employment; Unemployment; Statistical Significance + Suchen Sie Ihr Suchwort? Programme evaluation; Programmevaluation; Erprobung; Dienstverhältnis; Arbeitslosigkeit
Abstract	This article presents a creative and practical process for dealing with the problem of selection bias. Taking an algorithmic approach and capitalizing on the known treatment-associated variance in the X matrix, we propose a data transformation that allows estimating unbiased treatment effects. The approach does not call for modelling the data, based on underlying theories or assumptions about the selection process, but instead calls for using the existing variability within the data and letting the data speak. We illustrate with an application of the method to Italian Job Centres. (Contains 4 figures, 3 tables and 2 notes.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10