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Showing 1 to 15 of 16 results Save | Export
Erin W. Post – ProQuest LLC, 2024
Multivariate count data is ubiquitous in many areas of research including the physical, biological, and social sciences. These data are traditionally modeled with the Dirichlet Multinomial distribution (DM). A new, more flexible Dirichlet-Tree Multinomial (DTM) model is gaining in popularity. Here, we consider Bayesian DTM regression models. Our…
Descriptors: Regression (Statistics), Multivariate Analysis, Statistical Distributions, Bayesian Statistics
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Mangino, Anthony A.; Smith, Kendall A.; Finch, W. Holmes; Hernández-Finch, Maria E. – Measurement and Evaluation in Counseling and Development, 2022
A number of machine learning methods can be employed in the prediction of suicide attempts. However, many models do not predict new cases well in cases with unbalanced data. The present study improved prediction of suicide attempts via the use of a generative adversarial network.
Descriptors: Prediction, Suicide, Artificial Intelligence, Networks
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Allen, Jeff – Applied Measurement in Education, 2017
Using a sample of schools testing annually in grades 9-11 with a vertically linked series of assessments, a latent growth curve model is used to model test scores with student intercepts and slopes nested within school. Missed assessments can occur because of student mobility, student dropout, absenteeism, and other reasons. Missing data…
Descriptors: Achievement Gains, Academic Achievement, Growth Models, Scores
Lockwood, J. R.; Castellano, Katherine E. – Educational and Psychological Measurement, 2017
Student Growth Percentiles (SGPs) increasingly are being used in the United States for inferences about student achievement growth and educator effectiveness. Emerging research has indicated that SGPs estimated from observed test scores have large measurement errors. As such, little is known about "true" SGPs, which are defined in terms…
Descriptors: Item Response Theory, Correlation, Student Characteristics, Academic Achievement
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Stone, Clement A.; Tang, Yun – Practical Assessment, Research & Evaluation, 2013
Propensity score applications are often used to evaluate educational program impact. However, various options are available to estimate both propensity scores and construct comparison groups. This study used a student achievement dataset with commonly available covariates to compare different propensity scoring estimation methods (logistic…
Descriptors: Comparative Analysis, Probability, Sample Size, Program Evaluation
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Hofer, Sarah I. – International Journal of Science Education, 2015
The existence of gender-STEM (science, technology, engineering, and mathematics) stereotypes has been repeatedly documented. This article examines physics teachers' gender bias in grading and the influence of teaching experience in Switzerland, Austria, and Germany. In a 2?×?2 between-subjects design, with years of teaching experience included as…
Descriptors: Gender Bias, Physics, Generalization, Gender Differences
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Wang, Qiu; Diemer, Matthew A.; Maier, Kimberly S. – Educational and Psychological Measurement, 2013
This study integrated Bayesian hierarchical modeling and receiver operating characteristic analysis (BROCA) to evaluate how interest strength (IS) and interest differentiation (ID) predicted low–socioeconomic status (SES) youth's interest-major congruence (IMC). Using large-scale Kuder Career Search online-assessment data, this study fit three…
Descriptors: Bayesian Statistics, Socioeconomic Status, Student Interests, Gender Differences
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Cepeda-Cuervo, Edilberto; Núñez-Antón, Vicente – Journal of Educational and Behavioral Statistics, 2013
In this article, a proposed Bayesian extension of the generalized beta spatial regression models is applied to the analysis of the quality of education in Colombia. We briefly revise the beta distribution and describe the joint modeling approach for the mean and dispersion parameters in the spatial regression models' setting. Finally, we motivate…
Descriptors: Regression (Statistics), Foreign Countries, Educational Quality, Educational Research
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Petscher, Yaacov; Kershaw, Sarah; Koon, Sharon; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
Districts and schools use progress monitoring to assess student progress, to identify students who fail to respond to intervention, and to further adapt instruction to student needs. Researchers and practitioners often use progress monitoring data to estimate student achievement growth (slope) and evaluate changes in performance over time for…
Descriptors: Reading Comprehension, Reading Achievement, Elementary School Students, Secondary School Students
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Petscher, Yaacov; Kershaw, Sarah; Koon, Sharon; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
Districts and schools use progress monitoring to assess student progress, to identify students who fail to respond to intervention, and to further adapt instruction to student needs. Researchers and practitioners often use progress monitoring data to estimate student achievement growth (slope) and evaluate changes in performance over time for…
Descriptors: Response to Intervention, Achievement Gains, High Stakes Tests, Prediction
Tuttle, Christina Clark; Gleason, Philip; Knechtel, Virginia; Nichols-Barrer, Ira; Booker, Kevin; Chojnacki, Gregory; Coen, Thomas; Goble, Lisbeth – Mathematica Policy Research, Inc., 2015
KIPP (Knowledge is Power Program) is a national network of public charter schools whose stated mission is to help underserved students enroll in and graduate from college. Prior studies (see Tuttle et al. 2013) have consistently found that attending a KIPP middle school positively affects student achievement, but few have addressed longer-term…
Descriptors: Program Effectiveness, Program Evaluation, Academic Achievement, Charter Schools
Tuttle, Christina Clark; Gleason, Philip; Knechtel, Virginia; Nichols-Barrer, Ira; Booker, Kevin; Chojnacki, Gregory; Coen, Thomas; Goble, Lisbeth – Mathematica Policy Research, Inc., 2015
KIPP (Knowledge is Power Program) is a national network of public charter schools whose stated mission is to help underserved students enroll in and graduate from college. Prior studies (see Tuttle et al. 2013) have consistently found that attending a KIPP middle school positively affects student achievement, but few have addressed longer-term…
Descriptors: Program Effectiveness, Program Evaluation, Academic Achievement, Charter Schools
Tuttle, Christina Clark; Gleason, Philip; Knechtel, Virginia; Nichols-Barrer, Ira; Booker, Kevin; Chojnacki, Gregory; Coen, Thomas; Goble, Lisbeth – Mathematica Policy Research, Inc., 2015
KIPP (Knowledge is Power Program) is a national network of public charter schools whose stated mission is to help underserved students enroll in and graduate from college. Prior studies (see Tuttle et al. 2013) have consistently found that attending a KIPP middle school positively affects student achievement, but few have addressed longer-term…
Descriptors: Academic Achievement, Charter Schools, Educational Innovation, Institutional Characteristics
Karabatsos, George; Walker, Stephen G. – Society for Research on Educational Effectiveness, 2011
Karabatsos and Walker (2011) introduced a new Bayesian nonparametric (BNP) regression model. Through analyses of real and simulated data, they showed that the BNP regression model outperforms other parametric and nonparametric regression models of common use, in terms of predictive accuracy of the outcome (dependent) variable. The other,…
Descriptors: Bayesian Statistics, Regression (Statistics), Nonparametric Statistics, Statistical Inference
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Vaughn, Brandon K. – Journal on School Educational Technology, 2008
This study considers the importance of contextual effects on the quality of assessments on item bias and differential item functioning (DIF) in measurement. Often, in educational studies, students are clustered in teachers or schools, and the clusters could impact psychometric issues yet are largely ignored by traditional item analyses. A…
Descriptors: Test Bias, Educational Assessment, Educational Quality, Context Effect
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