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Autor/inn/enReardon, Sean F.; Raudenbush, Stephen W.
TitelUnder What Assumptions Do Site-by-Treatment Instruments Identify Average Causal Effects?
Quelle42 (2013) 2, S.143-163 (45 Seiten)Infoseite zur Zeitschrift
PDF als Volltext (1); PDF als Volltext kostenfreie Datei (2) Verfügbarkeit 
ZusatzinformationWeitere Informationen
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
DOI10.1177/0049124113494575
SchlagwörterCausal Models; Measures (Individuals); Research Design; Context Effect; Compliance (Psychology); Computation; Randomized Controlled Trials; Statistical Bias; Identification
AbstractThe increasing availability of data from multi-site randomized trials provides a potential opportunity to use instrumental variables methods to study the effects of multiple hypothesized mediators of the effect of a treatment. We derive nine assumptions needed to identify the effects of multiple mediators when using site-by-treatment interactions to generate multiple instruments. Three of these assumptions are unique to the multiple-site, multiple-mediator case: 1) the assumption that the mediators act in parallel (no mediator affects another mediator); 2) the assumption that the site-average effect of the treatment on each mediator is independent of the site-average effect of each mediator on the outcome; and 3) the assumption that the site-by-compliance matrix has sufficient rank. The first two of these assumptions are non-trivial and cannot be empirically verified, suggesting that multiple-site, multiple-mediator instrumental variables models must be justified by strong theory. The following are appended: (1) Rationale for the Parallel Mediators Assumption; (2) Mean and Variance of MSMM-IV Estimations; and (3) Expressions for the Between-Site Compliance-Effect Covariance when P = 1 or P = 2. [This article was published in "Sociological Methods and Research," v42 n2 p143-163 May 2013.] (As Provided).
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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