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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
Wallin, Gabriel; Wiberg, Marie – Journal of Educational and Behavioral Statistics, 2019
When equating two test forms, the equated scores will be biased if the test groups differ in ability. To adjust for the ability imbalance between nonequivalent groups, a set of common items is often used. When no common items are available, it has been suggested to use covariates correlated with the test scores instead. In this article, we reduce…
Descriptors: Equated Scores, Test Items, Probability, College Entrance Examinations
Lyu, Weicong; Kim, Jee-Seon; Suk, Youmi – Journal of Educational and Behavioral Statistics, 2023
This article presents a latent class model for multilevel data to identify latent subgroups and estimate heterogeneous treatment effects. Unlike sequential approaches that partition data first and then estimate average treatment effects (ATEs) within classes, we employ a Bayesian procedure to jointly estimate mixing probability, selection, and…
Descriptors: Hierarchical Linear Modeling, Bayesian Statistics, Causal Models, Statistical Inference
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
Grilli, Leonardo; Mealli, Fabrizia – Journal of Educational and Behavioral Statistics, 2008
The authors propose a methodology based on the principal strata approach to causal inference for assessing the relative effectiveness of two degree programs with respect to the employment status of their graduates. An innovative use of nonparametric bounds in the principal strata framework is shown, examining the role of some assumptions in…
Descriptors: Political Science, Employment Level, Outcomes of Education, Nonparametric Statistics
Fox, Jean-Paul – Journal of Educational and Behavioral Statistics, 2005
The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by an item response theory (IRT) model. The RR…
Descriptors: Item Response Theory, Models, Probability, Markov Processes
Van den Noortgate, Wim; De Boeck, Paul – Journal of Educational and Behavioral Statistics, 2005
Although differential item functioning (DIF) theory traditionally focuses on the behavior of individual items in two (or a few) specific groups, in educational measurement contexts, it is often plausible to regard the set of items as a random sample from a broader category. This article presents logistic mixed models that can be used to model…
Descriptors: Test Bias, Item Response Theory, Educational Assessment, Mathematical Models