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Lu, Jiannan; Ding, Peng; Dasgupta, Tirthankar – Journal of Educational and Behavioral Statistics, 2018
Assessing the causal effects of interventions on ordinal outcomes is an important objective of many educational and behavioral studies. Under the potential outcomes framework, we can define causal effects as comparisons between the potential outcomes under treatment and control. However, unfortunately, the average causal effect, often the…
Descriptors: Outcomes of Treatment, Mathematical Applications, Probability, Behavioral Science Research
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Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2013
This article examines the estimation of two-stage clustered designs for education randomized control trials (RCTs) using the nonparametric Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and control group outcomes are considered to be fixed for…
Descriptors: Computation, Causal Models, Statistical Inference, Nonparametric Statistics