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Steiner, Peter M.; Wong, Vivian – Society for Research on Educational Effectiveness, 2016
Despite recent emphasis on the use of randomized control trials (RCTs) for evaluating education interventions, in most areas of education research, observational methods remain the dominant approach for assessing program effects. Over the last three decades, the within-study comparison (WSC) design has emerged as a method for evaluating the…
Descriptors: Randomized Controlled Trials, Comparative Analysis, Research Design, Evaluation Methods
Steiner, Peter M.; Cook, Thomas D.; Li, Wei; Clark, M. H. – Journal of Research on Educational Effectiveness, 2015
In observational studies, selection bias will be completely removed only if the selection mechanism is ignorable, namely, all confounders of treatment selection and potential outcomes are reliably measured. Ideally, well-grounded substantive theories about the selection process and outcome-generating model are used to generate the sample of…
Descriptors: Quasiexperimental Design, Bias, Selection, Observation
Kim, Jee-Seon; Steiner, Peter M.; Hall, Courtney; Thoemmes, Felix – Society for Research on Educational Effectiveness, 2013
When randomized experiments cannot be conducted in practice, propensity score (PS) techniques for matching treated and control units are frequently used for estimating causal treatment effects from observational data. Despite the popularity of PS techniques, they are not yet well studied for matching multilevel data where selection into treatment…
Descriptors: Probability, Research Methodology, Control Groups, Experimental Groups
Keller, Bryan S. B.; Kim, Jee-Seon; Steiner, Peter M. – Society for Research on Educational Effectiveness, 2013
Propensity score analysis (PSA) is a methodological technique which may correct for selection bias in a quasi-experiment by modeling the selection process using observed covariates. Because logistic regression is well understood by researchers in a variety of fields and easy to implement in a number of popular software packages, it has…
Descriptors: Probability, Scores, Statistical Analysis, Statistical Bias
Steiner, Peter M.; Cook, Thomas D.; Shadish, William R.; Clark, M. H. – Psychological Methods, 2010
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…
Descriptors: Selection, Bias, Observation, Comparative Analysis

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