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Benjamin Lu; Eli Ben-Michael; Avi Feller; Luke Miratrix – Journal of Educational and Behavioral Statistics, 2023
In multisite trials, learning about treatment effect variation across sites is critical for understanding where and for whom a program works. Unadjusted comparisons, however, capture "compositional" differences in the distributions of unit-level features as well as "contextual" differences in site-level features, including…
Descriptors: Statistical Analysis, Statistical Distributions, Program Implementation, Comparative Analysis
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Suk, Youmi; Steiner, Peter M.; Kim, Jee-Seon; Kang, Hyunseung – Journal of Educational and Behavioral Statistics, 2022
Regression discontinuity (RD) designs are commonly used for program evaluation with continuous treatment assignment variables. But in practice, treatment assignment is frequently based on ordinal variables. In this study, we propose an RD design with an ordinal running variable to assess the effects of extended time accommodations (ETA) for…
Descriptors: Regression (Statistics), Program Evaluation, Research Design, English Language Learners
Hedges, Larry V.; Schauer, Jacob M. – Journal of Educational and Behavioral Statistics, 2019
The problem of assessing whether experimental results can be replicated is becoming increasingly important in many areas of science. It is often assumed that assessing replication is straightforward: All one needs to do is repeat the study and see whether the results of the original and replication studies agree. This article shows that the…
Descriptors: Replication (Evaluation), Research Design, Research Methodology, Program Evaluation
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Hong, Guanglei; Qin, Xu; Yang, Fan – Journal of Educational and Behavioral Statistics, 2018
Through a sensitivity analysis, the analyst attempts to determine whether a conclusion of causal inference could be easily reversed by a plausible violation of an identification assumption. Analytic conclusions that are harder to alter by such a violation are expected to add a higher value to scientific knowledge about causality. This article…
Descriptors: Statistical Inference, Probability, Statistical Bias, Statistical Analysis
Feller, Avi; Mealli, Fabrizia; Miratrix, Luke – Journal of Educational and Behavioral Statistics, 2017
Researchers addressing posttreatment complications in randomized trials often turn to principal stratification to define relevant assumptions and quantities of interest. One approach for the subsequent estimation of causal effects in this framework is to use methods based on the "principal score," the conditional probability of belonging…
Descriptors: Scores, Probability, Computation, Program Evaluation
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Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2011
For RCTs of education interventions, it is often of interest to estimate associations between student and mediating teacher practice outcomes, to examine the extent to which the study's conceptual model is supported by the data, and to identify specific mediators that are most associated with student learning. This article develops statistical…
Descriptors: Least Squares Statistics, Intervention, Academic Achievement, Correlation
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Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2008
This article examines theoretical and empirical issues related to the statistical power of impact estimates for experimental evaluations of education programs. The author considers designs where random assignment is conducted at the school, classroom, or student level, and employs a unified analytic framework using statistical methods from the…
Descriptors: Elementary School Students, Research Design, Standardized Tests, Program Evaluation
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Zanutto, Elaine; Lu, Bo; Hornick, Robert – Journal of Educational and Behavioral Statistics, 2005
In 1998, the U.S. Office of National Drug Control Policy launched a national media campaign in an effort to reduce and prevent drug use among young Americans. Because the campaign was implemented nationwide, there is no control group available for use in evaluating the effects of the campaign. Nevertheless, it is possible to use propensity score…
Descriptors: Drug Use, Prevention, Program Effectiveness, Classification
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Marcus, Sue M. – Journal of Educational and Behavioral Statistics, 1997
A method is presented that uses omitted variable bias to assess the uncertainty of the hidden bias in estimation of a treatment effect by describing the scenarios regarding the unobserved covariate that can lead to a given level of hidden bias. The evaluation of two AIDS education programs illustrates the method. (SLD)
Descriptors: Acquired Immune Deficiency Syndrome, Estimation (Mathematics), Health Education, Outcomes of Education