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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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Kuijpers, Renske E.; Visser, Ingmar; Molenaar, Dylan – Journal of Educational and Behavioral Statistics, 2021
Mixture models have been developed to enable detection of within-subject differences in responses and response times to psychometric test items. To enable mixture modeling of both responses and response times, a distributional assumption is needed for the within-state response time distribution. Since violations of the assumed response time…
Descriptors: Test Items, Responses, Reaction Time, Models
Shear, Benjamin R.; Reardon, Sean F. – Journal of Educational and Behavioral Statistics, 2021
This article describes an extension to the use of heteroskedastic ordered probit (HETOP) models to estimate latent distributional parameters from grouped, ordered-categorical data by pooling across multiple waves of data. We illustrate the method with aggregate proficiency data reporting the number of students in schools or districts scoring in…
Descriptors: Statistical Analysis, Computation, Regression (Statistics), Sample Size
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Kleinke, Kristian – Journal of Educational and Behavioral Statistics, 2017
Predictive mean matching (PMM) is a standard technique for the imputation of incomplete continuous data. PMM imputes an actual observed value, whose predicted value is among a set of k = 1 values (the so-called donor pool), which are closest to the one predicted for the missing case. PMM is usually better able to preserve the original distribution…
Descriptors: Statistical Analysis, Statistical Distributions, Robustness (Statistics), Sample Size
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Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2017
An increasing concern of producers of educational assessments is fraudulent behavior during the assessment (van der Linden, 2009). Benefiting from item preknowledge (e.g., Eckerly, 2017; McLeod, Lewis, & Thissen, 2003) is one type of fraudulent behavior. This article suggests two new test statistics for detecting individuals who may have…
Descriptors: Test Items, Cheating, Testing Problems, Identification
Reardon, Sean F.; Shear, Benjamin R.; Castellano, Katherine E.; Ho, Andrew D. – Journal of Educational and Behavioral Statistics, 2017
Test score distributions of schools or demographic groups are often summarized by frequencies of students scoring in a small number of ordered proficiency categories. We show that heteroskedastic ordered probit (HETOP) models can be used to estimate means and standard deviations of multiple groups' test score distributions from such data. Because…
Descriptors: Scores, Statistical Analysis, Models, Computation
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Schweig, Jonathan – Journal of Educational and Behavioral Statistics, 2014
Measures of classroom environments have become central to policy efforts that assess school and teacher quality. This has sparked a wide interest in using multilevel factor analysis to test measurement hypotheses about classroom-level variables. One approach partitions the total covariance matrix and tests models separately on the…
Descriptors: Factor Analysis, Robustness (Statistics), Measurement, Classroom Environment
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Jozwiak, Katarzyna; Moerbeek, Mirjam – Journal of Educational and Behavioral Statistics, 2012
Studies on event occurrence aim to investigate if and when subjects experience a particular event. The timing of events may be measured continuously using thin precise units or discretely using time periods. The latter metric of time is often used in social science research and the generalized linear model (GLM) is an appropriate model for data…
Descriptors: Statistical Analysis, Time, Sample Size, Social Science Research
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Karl, Andrew T.; Yang, Yan; Lohr, Sharon L. – Journal of Educational and Behavioral Statistics, 2013
Value-added models have been widely used to assess the contributions of individual teachers and schools to students' academic growth based on longitudinal student achievement outcomes. There is concern, however, that ignoring the presence of missing values, which are common in longitudinal studies, can bias teachers' value-added scores.…
Descriptors: Evaluation Methods, Teacher Effectiveness, Academic Achievement, Achievement Gains
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Verkuilen, Jay; Smithson, Michael – Journal of Educational and Behavioral Statistics, 2012
Doubly bounded continuous data are common in the social and behavioral sciences. Examples include judged probabilities, confidence ratings, derived proportions such as percent time on task, and bounded scale scores. Dependent variables of this kind are often difficult to analyze using normal theory models because their distributions may be quite…
Descriptors: Responses, Regression (Statistics), Statistical Analysis, Models
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von Davier, Alina A.; Kong, Nan – Journal of Educational and Behavioral Statistics, 2005
This article describes a new, unified framework for linear equating in a non-equivalent groups anchor test (NEAT) design. The authors focus on three methods for linear equating in the NEAT design--Tucker, Levine observed-score, and chain--and develop a common parameterization that shows that each particular equating method is a special case of the…
Descriptors: Equations (Mathematics), Sample Size, Statistical Distributions, Error of Measurement