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McNeish, Daniel – Educational and Psychological Measurement, 2017
In behavioral sciences broadly, estimating growth models with Bayesian methods is becoming increasingly common, especially to combat small samples common with longitudinal data. Although Mplus is becoming an increasingly common program for applied research employing Bayesian methods, the limited selection of prior distributions for the elements of…
Descriptors: Models, Bayesian Statistics, Statistical Analysis, Computer Software
Luo, Yong; Jiao, Hong – Educational and Psychological Measurement, 2018
Stan is a new Bayesian statistical software program that implements the powerful and efficient Hamiltonian Monte Carlo (HMC) algorithm. To date there is not a source that systematically provides Stan code for various item response theory (IRT) models. This article provides Stan code for three representative IRT models, including the…
Descriptors: Bayesian Statistics, Item Response Theory, Probability, Computer Software
Lavbic, Dejan; Matek, Tadej; Zrnec, Aljaž – Interactive Learning Environments, 2017
Today's software industry requires individuals who are proficient in as many programming languages as possible. Structured query language (SQL), as an adopted standard, is no exception, as it is the most widely used query language to retrieve and manipulate data. However, the process of learning SQL turns out to be challenging. The need for a…
Descriptors: Evaluation Methods, Information Systems, Intelligent Tutoring Systems, Computer Science Education
McNeish, Daniel M. – Journal of Educational and Behavioral Statistics, 2016
Mixed-effects models (MEMs) and latent growth models (LGMs) are often considered interchangeable save the discipline-specific nomenclature. Software implementations of these models, however, are not interchangeable, particularly with small sample sizes. Restricted maximum likelihood estimation that mitigates small sample bias in MEMs has not been…
Descriptors: Models, Statistical Analysis, Hierarchical Linear Modeling, Sample Size
Huang, Hung-Yu; Wang, Wen-Chung – Educational and Psychological Measurement, 2014
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
Descriptors: Item Response Theory, Hierarchical Linear Modeling, Computation, Test Reliability
DeCarlo, Lawrence T. – Applied Psychological Measurement, 2011
Cognitive diagnostic models (CDMs) attempt to uncover latent skills or attributes that examinees must possess in order to answer test items correctly. The DINA (deterministic input, noisy "and") model is a popular CDM that has been widely used. It is shown here that a logistic version of the model can easily be fit with standard software for…
Descriptors: Bayesian Statistics, Computation, Cognitive Tests, Diagnostic Tests