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Steiner, Peter M.; Kim, Jee-Seon – Society for Research on Educational Effectiveness, 2015
Despite the popularity of propensity score (PS) techniques they are not yet well studied for matching multilevel data where selection into treatment takes place among level-one units within clusters. This paper suggests a PS matching strategy that tries to avoid the disadvantages of within- and across-cluster matching. The idea is to first…
Descriptors: Computation, Outcomes of Treatment, Multivariate Analysis, Probability
Kelcey, Benjamin – Society for Research on Educational Effectiveness, 2011
A central issue in nonexperimental studies is the identification of comparable individuals (e.g. students) to remove selection bias. One such increasingly common method to identify comparable individuals and address selection bias is the propensity score (PS). PS methods rely on a model of the treatment assignment to identify comparable…
Descriptors: Probability, Selection, Bias, Monte Carlo Methods
Tipton, Elizabeth; Sullivan, Kate; Hedges, Larry; Vaden-Kiernan, Michael; Borman, Geoffrey; Caverly, Sarah – Society for Research on Educational Effectiveness, 2011
In this paper the authors present a new method for sample selection for scale-up experiments. This method uses propensity score matching methods to create a sample that is similar in composition to a well-defined generalization population. The method they present is flexible and practical in the sense that it identifies units to be targeted for…
Descriptors: Sampling, Selection, Research Methodology, Reading Programs
Mokher, Christine; Cavalluzzo, Linda – Society for Research on Educational Effectiveness, 2011
This presentation focuses on the quasi-experimental methods used to select comparison schools for an evaluation of a federal investing in innovation (i3) validation grant. The Northeast Tennessee College and Career Ready Consortium (NETCO) consists of 29 high schools participating in a five-year program to expand students' access to rigorous…
Descriptors: Quasiexperimental Design, Probability, Grants, Intervention