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Yanagiura, Takeshi – Community College Review, 2023
Objective: This study examines how accurately a small set of short-term academic indicators can approximate long-term outcomes of community college students so that decision-makers can take informed actions based on those indicators to evaluate the current progress of large-scale reform efforts on long-term outcomes, which in practice will not be…
Descriptors: Community Colleges, Community College Students, Educational Indicators, Outcomes of Education
Cutler, David M.; Meara, Ellen; Richards-Shubik, Seth – Journal of Human Resources, 2012
We develop a model of induced innovation that applies to medical research. Our model yields three empirical predictions. First, initial death rates and subsequent research effort should be positively correlated. Second, research effort should be associated with more rapid mortality declines. Third, as a byproduct of targeting the most common…
Descriptors: Evidence, Innovation, Medical Services, Infants
Lichtman, Marilyn; And Others – 1979
Although a number of studies have been conducted to examine the status attainment process, very few have focused on differences in educational attainment for black, white, and Hispanic females. The primary purpose of this study was to test predictive models of attainment for these subgroups. Variables considered potentially important to the…
Descriptors: Educational Attainment, Females, High School Graduates, Longitudinal Studies
Peer reviewedNettles, Michael T.; And Others – Journal of Higher Education, 1986
Racial differences in the effects of intellectual and nonintellectual student characteristics and faculty attitudes and behaviors that significantly predict students' college performance are examined. Significant differences between black and white students' college performance and the predictors are discovered. (Author/MLW)
Descriptors: Academic Achievement, Black Students, College Students, Comparative Analysis
Chang, Lin – New Directions for Institutional Research, 2006
Data-mining technology's predictive modeling was applied to enhance the prediction of enrollment behaviors of admitted applicants at a large state university. (Contains 4 tables and 6 figures.)
Descriptors: College Admission, Data Collection, Data Analysis, Models

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