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Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – Annenberg Institute for School Reform at Brown University, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Higher Education, Predictive Measurement, Models
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Bai, Haiyan – Journal of Experimental Education, 2013
Propensity score estimation plays a fundamental role in propensity score matching for reducing group selection bias in observational data. To increase the accuracy of propensity score estimation, the author developed a bootstrap propensity score. The commonly used propensity score matching methods: nearest neighbor matching, caliper matching, and…
Descriptors: Statistical Inference, Sampling, Probability, Computation
Brick, J. Michael; And Others – 1996
The National Household Education Survey (NHES) is a data collection system of the National Center for Education Statistics. The NHES is a telephone survey of the noninstitutionalized civilian population using households selected using random digit dialing methods. Approximately 60,000 households are screened for each administration, and people who…
Descriptors: Data Collection, National Surveys, Probability, Research Methodology
Ingels, Steven J.; Quinn, Peggy – 1996
The National Education Longitudinal Studies Program (NELS) is a long-term effort that encompasses the educational experience of youth from three decades. This report is based on the National Education Longitudinal Study of 1988 (NELS:88), a component of the NELS series that began as a national probability sample of eighth grade schools and…
Descriptors: Data Analysis, Educational Experience, Elementary Secondary Education, Eligibility