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Joemari Olea; Kevin Carl Santos – Journal of Educational and Behavioral Statistics, 2024
Although the generalized deterministic inputs, noisy "and" gate model (G-DINA; de la Torre, 2011) is a general cognitive diagnosis model (CDM), it does not account for the heterogeneity that is rooted from the existing latent groups in the population of examinees. To address this, this study proposes the mixture G-DINA model, a CDM that…
Descriptors: Cognitive Measurement, Models, Algorithms, Simulation
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Liu, Jin – Journal of Educational and Behavioral Statistics, 2022
Longitudinal data analysis has been widely employed to examine between-individual differences in within-individual changes. One challenge of such analyses is that the rate-of-change is only available indirectly when change patterns are nonlinear with respect to time. Latent change score models (LCSMs), which can be employed to investigate the…
Descriptors: Longitudinal Studies, Individual Differences, Scores, Models
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Joshua B. Gilbert; Luke W. Miratrix; Mridul Joshi; Benjamin W. Domingue – Journal of Educational and Behavioral Statistics, 2025
Analyzing heterogeneous treatment effects (HTEs) plays a crucial role in understanding the impacts of educational interventions. A standard practice for HTE analysis is to examine interactions between treatment status and preintervention participant characteristics, such as pretest scores, to identify how different groups respond to treatment.…
Descriptors: Causal Models, Item Response Theory, Statistical Inference, Psychometrics
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Trendtel, Matthias; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2021
A multidimensional Bayesian item response model is proposed for modeling item position effects. The first dimension corresponds to the ability that is to be measured; the second dimension represents a factor that allows for individual differences in item position effects called persistence. This model allows for nonlinear item position effects on…
Descriptors: Bayesian Statistics, Item Response Theory, Test Items, Test Format
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Debeer, Dries; Buchholz, Janine; Hartig, Johannes; Janssen, Rianne – Journal of Educational and Behavioral Statistics, 2014
In this article, the change in examinee effort during an assessment, which we will refer to as persistence, is modeled as an effect of item position. A multilevel extension is proposed to analyze hierarchically structured data and decompose the individual differences in persistence. Data from the 2009 Program of International Student Achievement…
Descriptors: Reading Tests, International Programs, Testing Programs, Individual Differences
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Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan – Journal of Educational and Behavioral Statistics, 2011
In this article, we consider estimation of parameters of random effects models from samples collected via complex multistage designs. Incorporation of sampling weights is one way to reduce estimation bias due to unequal probabilities of selection. Several weighting methods have been proposed in the literature for estimating the parameters of…
Descriptors: Sampling, Computation, Statistical Bias, Statistical Analysis
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von Davier, Matthias; Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2010
This article presents an application of a stochastic approximation expectation maximization (EM) algorithm using a Metropolis-Hastings (MH) sampler to estimate the parameters of an item response latent regression model. Latent regression item response models are extensions of item response theory (IRT) to a latent variable model with covariates…
Descriptors: Item Response Theory, Statistical Analysis, Regression (Statistics), Models
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Li, Deping; Oranje, Andreas; Jiang, Yanlin – Journal of Educational and Behavioral Statistics, 2009
To find population proficiency distributions, a two-level hierarchical linear model may be applied to large-scale survey assessments such as the National Assessment of Educational Progress (NAEP). The model and parameter estimation are developed and a simulation was carried out to evaluate parameter recovery. Subsequently, both a hierarchical and…
Descriptors: Computation, National Competency Tests, Measurement, Regression (Statistics)