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Shin, Yongyun – Journal of Educational and Behavioral Statistics, 2012
Does reduced class size cause higher academic achievement for both Black and other students in reading, mathematics, listening, and word recognition skills? Do Black students benefit more than other students from reduced class size? Does the magnitude of the minority advantages vary significantly across schools? This article addresses the causal…
Descriptors: African American Students, Class Size, Recognition (Achievement), Causal Models
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von Davier, Alina A. – Journal of Educational and Behavioral Statistics, 2008
The two most common observed-score equating functions are the linear and equipercentile functions. These are often seen as different methods, but von Davier, Holland, and Thayer showed that any equipercentile equating function can be decomposed into linear and nonlinear parts. They emphasized the dominant role of the linear part of the nonlinear…
Descriptors: Equated Scores, Causal Models, Structural Equation Models, Data Collection
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Wainer, Howard – Journal of Educational and Behavioral Statistics, 2010
In this essay, the author tries to look forward into the 21st century to divine three things: (i) What skills will researchers in the future need to solve the most pressing problems? (ii) What are some of the most likely candidates to be those problems? and (iii) What are some current areas of research that seem mined out and should not distract…
Descriptors: Research Skills, Researchers, Internet, Access to Information
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Gitelman, Alix I. – Journal of Educational and Behavioral Statistics, 2005
In group-allocation studies for comparing behavioral, social, or educational interventions, subjects in the same group necessarily receive the same treatment, whereby a group and/or group-dynamic effect can confound the treatment effect. General counterfactual outcomes that depend on group characteristics, group membership, and treatment are…
Descriptors: Computation, Causal Models, Intervention, Group Membership
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Briggs, Derek C. – Journal of Educational and Behavioral Statistics, 2004
In the social sciences, evaluating the effectiveness of a program or intervention often leads researchers to draw causal inferences from observational research designs. Bias in estimated causal effects becomes an obvious problem in such settings. This article presents the Heckman Model as an approach sometimes applied to observational data for the…
Descriptors: Social Science Research, Statistical Inference, Causal Models, Test Bias