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Bartolucci, Francesco; Pennoni, Fulvia; Vittadini, Giorgio – Journal of Educational and Behavioral Statistics, 2016
We extend to the longitudinal setting a latent class approach that was recently introduced by Lanza, Coffman, and Xu to estimate the causal effect of a treatment. The proposed approach enables an evaluation of multiple treatment effects on subpopulations of individuals from a dynamic perspective, as it relies on a latent Markov (LM) model that is…
Descriptors: Causal Models, Markov Processes, Longitudinal Studies, Probability
Ho, Andrew D.; Reardon, Sean F. – Journal of Educational and Behavioral Statistics, 2012
Test scores are commonly reported in a small number of ordered categories. Examples of such reporting include state accountability testing, Advanced Placement tests, and English proficiency tests. This article introduces and evaluates methods for estimating achievement gaps on a familiar standard-deviation-unit metric using data from these ordered…
Descriptors: Achievement Gap, Scores, Computation, Classification
Reardon, Sean F.; Ho, Andrew D. – Journal of Educational and Behavioral Statistics, 2015
In an earlier paper, we presented methods for estimating achievement gaps when test scores are coarsened into a small number of ordered categories, preventing fine-grained distinctions between individual scores. We demonstrated that gaps can nonetheless be estimated with minimal bias across a broad range of simulated and real coarsened data…
Descriptors: Achievement Gap, Performance Factors, Educational Practices, Scores
Guo, Hongwen; Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2011
Nonparametric or kernel regression estimation of item response curves (IRCs) is often used in item analysis in testing programs. These estimates are biased when the observed scores are used as the regressor because the observed scores are contaminated by measurement error. Accuracy of this estimation is a concern theoretically and operationally.…
Descriptors: Testing Programs, Measurement, Item Analysis, Error of Measurement
Ho, Andrew Dean – Journal of Educational and Behavioral Statistics, 2009
Problems of scale typically arise when comparing test score trends, gaps, and gap trends across different tests. To overcome some of these difficulties, test score distributions on the same score scale can be represented by nonparametric graphs or statistics that are invariant under monotone scale transformations. This article motivates and then…
Descriptors: Nonparametric Statistics, Comparative Analysis, Trend Analysis, Scores

Rossi, Natasha; Wang, Xiaohui; Ramsay, James O. – Journal of Educational and Behavioral Statistics, 2002
Combined several developments in statistics and item response theory to develop a procedure for analysis of dichotomously scored test data. This version of nonparametric item response analysis, as illustrated through simulation and with data from other studies, marginalizes the role of the ability parameter theta. (SLD)
Descriptors: Ability, Item Response Theory, Nonparametric Statistics, Scores