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Sales, Adam C.; Hansen, Ben B.; Rowan, Brian – Journal of Educational and Behavioral Statistics, 2018
In causal matching designs, some control subjects are often left unmatched, and some covariates are often left unmodeled. This article introduces "rebar," a method using high-dimensional modeling to incorporate these commonly discarded data without sacrificing the integrity of the matching design. After constructing a match, a researcher…
Descriptors: Computation, Prediction, Models, Data
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Tipton, Elizabeth – Journal of Educational and Behavioral Statistics, 2013
As a result of the use of random assignment to treatment, randomized experiments typically have high internal validity. However, units are very rarely randomly selected from a well-defined population of interest into an experiment; this results in low external validity. Under nonrandom sampling, this means that the estimate of the sample average…
Descriptors: Generalization, Experiments, Classification, Computation
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Douglas, Karen M.; Mislevy, Robert J. – Journal of Educational and Behavioral Statistics, 2010
Important decisions about students are made by combining multiple measures using complex decision rules. Although methods for characterizing the accuracy of decisions based on a single measure have been suggested by numerous researchers, such methods are not useful for estimating the accuracy of decisions based on multiple measures. This study…
Descriptors: Educational Development, Test Use, Classification, Computation