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Ames, Allison J.; Myers, Aaron J. – Educational and Psychological Measurement, 2021
Contamination of responses due to extreme and midpoint response style can confound the interpretation of scores, threatening the validity of inferences made from survey responses. This study incorporated person-level covariates in the multidimensional item response tree model to explain heterogeneity in response style. We include an empirical…
Descriptors: Response Style (Tests), Item Response Theory, Longitudinal Studies, Adolescents
Liu, Yang; Wang, Xiaojing – Journal of Educational and Behavioral Statistics, 2020
Parametric methods, such as autoregressive models or latent growth modeling, are usually inflexible to model the dependence and nonlinear effects among the changes of latent traits whenever the time gap is irregular and the recorded time points are individually varying. Often in practice, the growth trend of latent traits is subject to certain…
Descriptors: Bayesian Statistics, Nonparametric Statistics, Regression (Statistics), Item Response Theory
Smith, Lindsey J. Wolff; Beretvas, S. Natasha – Journal of Experimental Education, 2017
Conventional multilevel modeling works well with purely hierarchical data; however, pure hierarchies rarely exist in real datasets. Applied researchers employ ad hoc procedures to create purely hierarchical data. For example, applied educational researchers either delete mobile participants' data from the analysis or identify the student only with…
Descriptors: Student Mobility, Academic Achievement, Simulation, Influences
Hung, Lai-Fa; Wang, Wen-Chung – Journal of Educational and Behavioral Statistics, 2012
In the human sciences, ability tests or psychological inventories are often repeatedly conducted to measure growth. Standard item response models do not take into account possible autocorrelation in longitudinal data. In this study, the authors propose an item response model to account for autocorrelation. The proposed three-level model consists…
Descriptors: Item Response Theory, Correlation, Models, Longitudinal Studies
Kaplan, David; Depaoli, Sarah – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This article examines the problem of specification error in 2 models for categorical latent variables; the latent class model and the latent Markov model. Specification error in the latent class model focuses on the impact of incorrectly specifying the number of latent classes of the categorical latent variable on measures of model adequacy as…
Descriptors: Markov Processes, Longitudinal Studies, Probability, Item Response Theory
Jeon, Minjeong – ProQuest LLC, 2012
Maximum likelihood (ML) estimation of generalized linear mixed models (GLMMs) is technically challenging because of the intractable likelihoods that involve high dimensional integrations over random effects. The problem is magnified when the random effects have a crossed design and thus the data cannot be reduced to small independent clusters. A…
Descriptors: Hierarchical Linear Modeling, Computation, Measurement, Maximum Likelihood Statistics