A Statistical Model for Misreported Binary Outcomes in Clustered RCTs of Education Interventions

Autor/in	Schochet, Peter Z.
Titel	A Statistical Model for Misreported Binary Outcomes in Clustered RCTs of Education Interventions
Quelle	In: Journal of Educational and Behavioral Statistics, 38 (2013) 5, S.470-498 (29 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998613480393
Schlagwörter	Control Groups; Experimental Groups; Educational Research; Data Analysis; Outcomes of Treatment; Error Patterns; Statistical Analysis; Maximum Likelihood Statistics; Computation; Youth Programs; Disadvantaged Youth; Vocational Education; Adolescents; Young Adults; Student Surveys; Parent Surveys; Teacher Surveys; Student Records; Equations (Mathematics); Regression (Statistics); Models + Suchen Sie Ihr Suchwort? Bildungsforschung; Pädagogische Forschung; Auswertung; Fehlertyp; Statistische Analyse; Jugendsofortprogramm; Benachteiligter Jugendlicher; Ausbildung; Berufsbildung; Adolescent; Adolescence; Adoleszenz; Jugend; Jugendalter; Jugendlicher; Young adult; Junger Erwachsener; Schülerbefragung; Schülerakte; Equations; Mathematics; Gleichungslehre; Regression; Regressionsanalyse; Analogiemodell
Abstract	In education randomized control trials (RCTs), the misreporting of student outcome data could lead to biased estimates of average treatment effects (ATEs) and their standard errors. This article discusses a statistical model that adjusts for misreported binary outcomes for two-level, school-based RCTs, where it is assumed that misreporting could occur for students with truly undesirable outcomes, but not for those with truly desirable outcomes. A latent variable index approach using study baseline data is employed to model both the misreporting and binary outcome decision processes, separately for treatments and controls, using random effects probit models to adjust for school-level clustering. Quasi-Newton maximum likelihood methods are developed to obtain consistent estimates of the ATE parameter and the unobserved misreporting rates. The estimation approach is demonstrated using self-reported arrest data from a large-scale RCT of Job Corps, the nation's largest residential training program for disadvantaged youths between the ages of 16 and 24. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10