Peter M. Steiner

William R Shadish3
Thomas D Cook2
Sue M Marcus1
3William R Shadish
2Thomas D Cook
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The assumption of strongly ignorable treatment assignment is required for eliminating selection bias in observational studies. To meet this assumption, researchers often rely on a strategy of selecting covariates that they think will control for selection bias. Theory indicates that the most important covariates are those highly correlated with both the(More)
In this article, we review past studies comparing randomized experiments to regression discontinuity designs, mostly finding similar results, but with significant exceptions. The latter might be due to potential confounds of study characteristics with assignment method or with failure to estimate the same parameter over methods. In this study, we correct(More)
Although randomized studies have high internal validity, generalizability of the estimated causal effect from randomized clinical trials to real-world clinical or educational practice may be limited. We consider the implication of randomized assignment to treatment, as compared with choice of preferred treatment as it occurs in real-world conditions.(More)
Course Description Social scientists routinely ask causal questions. " Does job training cause higher earnings? " " Does divorce impede children's academic progress? " " Does No-Child-Left-Behind increase student achievement scores? " " Does retaining kindergartners for one year (instead of promoting them) impede their future achievements? " Questions such(More)
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