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50 Years of ERIC
50 Years of ERIC
The Education Resources Information Center (ERIC) is celebrating its 50th Birthday! First opened on May 15th, 1964 ERIC continues the long tradition of ongoing innovation and enhancement.

Learn more about the history of ERIC here. PDF icon

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Jin, Hui; Barnard, John; Rubin, Donald B. – Journal of Educational and Behavioral Statistics, 2010
Missing data, especially when coupled with noncompliance, are a challenge even in the setting of randomized experiments. Although some existing methods can address each complication, it can be difficult to handle both of them simultaneously. This is true in the example of the New York City School Choice Scholarship Program, where both the…
Descriptors: Urban Schools, School Choice, Scholarships, Principals
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Jin, Hui; Rubin, Donald B. – Journal of Educational and Behavioral Statistics, 2009
An approach to handle partial compliance behavior using principal stratification is presented and applied to a subset of the longitudinal data from the New York City School Choice Scholarship Program, a randomized experiment designed to assess the effects of private schools versus public schools on academic achievement. The initial analysis…
Descriptors: Statistical Inference, Causal Models, Longitudinal Studies, Public Schools
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Stuart, Elizabeth A.; Rubin, Donald B. – Journal of Educational and Behavioral Statistics, 2008
When estimating causal effects from observational data, it is desirable to approximate a randomized experiment as closely as possible. This goal can often be achieved by choosing a subsample from the original control group that matches the treatment group on the distribution of the observed covariates. However, sometimes the original control group…
Descriptors: Control Groups, Prevention, Program Effectiveness, Observation
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Rubin, Donald B.; Stuart, Elizabeth A.; Zanutto, Elaine L. – Journal of Educational and Behavioral Statistics, 2004
There has been substantial interest in recent years in the performance and accountability of teachers and schools, partially due to the No Child Left Behind legislation, which requires states to develop a system of sanctions and rewards to hold districts and schools accountable for academic achievement. This focus has lead to an increase in…
Descriptors: Federal Legislation, Test Results, Rewards, Sanctions
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Rubin, Donald B. – Journal of Educational and Behavioral Statistics, 2004
Inference for causal effects is a critical activity in many branches of science and public policy. The field of statistics is the one field most suited to address such problems, whether from designed experiments or observational studies. Consequently, it is arguably essential that departments of statistics teach courses in causal inference to both…
Descriptors: Undergraduate Students, Public Policy, Statistical Inference, Graduate Students
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Zhang, Junni L.; Rubin, Donald B. – Journal of Educational and Behavioral Statistics, 2003
The topic of "truncation by death" in randomized experiments arises in many fields, such as medicine, economics and education. Traditional approaches addressing this issue ignore the fact that the outcome after the truncation is neither "censored" nor "missing," but should be treated as being defined on an extended sample space. Using an…
Descriptors: Experiments, Predictor Variables, Bayesian Statistics, Death
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Mealli, Fabrizia; Rubin, Donald B. – Journal of Educational and Behavioral Statistics, 2002
Notes that the article reviewed contributes to the expanding literature on noncompliance by explicating the assumptions involving covariates that can be used to identify maximum likelihood estimates in place of exclusion restrictions. Notes points that require further discussion. (SLD)
Descriptors: Estimation (Mathematics), Intervention, Maximum Likelihood Statistics, Models
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Little, Roderick J. A.; Rubin, Donald B. – Journal of Educational and Behavioral Statistics, 1994
Equating a new standard test to an old reference test is considered when samples for equating are not randomly selected from the target population of test takers, identifying two problems from equating from biased samples. An empirical example with data from the Armed Services Vocational Aptitude Battery illustrates the approach. (SLD)
Descriptors: Equated Scores, Military Personnel, Sampling, Statistical Analysis