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ERIC Number: EJ1160773
Record Type: Journal
Publication Date: 2017-Dec
Pages: 33
Abstractor: As Provided
ISSN: ISSN-1076-9986
Principal Score Methods: Assumptions, Extensions, and Practical Considerations
Feller, Avi; Mealli, Fabrizia; Miratrix, Luke
Journal of Educational and Behavioral Statistics, v42 n6 p726-758 Dec 2017
Researchers addressing posttreatment complications in randomized trials often turn to principal stratification to define relevant assumptions and quantities of interest. One approach for the subsequent estimation of causal effects in this framework is to use methods based on the "principal score," the conditional probability of belonging to a certain principal stratum given covariates. These methods typically assume that stratum membership is as good as randomly assigned, given these covariates. We clarify the key assumption in this context, known as principal ignorability, and argue that versions of this assumption are quite strong in practice. We describe these concepts in terms of both one- and two-sided noncompliance and propose a novel approach for researchers to "mix and match" principal ignorability assumptions with alternative assumptions, such as the exclusion restriction. Finally, we apply these ideas to randomized evaluations of a job training program and an early childhood education program. Overall, applied researchers should acknowledge that principal score methods, while useful tools, rely on assumptions that are typically hard to justify in practice.
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Publication Type: Journal Articles; Reports - Research
Education Level: Early Childhood Education
Audience: N/A
Language: English
Sponsor: Institute of Education Sciences (ED)
Authoring Institution: N/A
IES Funded: Yes
Grant or Contract Numbers: R305D150040