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Hao, Jiangang; Ho, Tin Kam – Journal of Educational and Behavioral Statistics, 2019
Machine learning is a popular topic in data analysis and modeling. Many different machine learning algorithms have been developed and implemented in a variety of programming languages over the past 20 years. In this article, we first provide an overview of machine learning and clarify its difference from statistical inference. Then, we review…
Descriptors: Artificial Intelligence, Statistical Inference, Data Analysis, Programming Languages
Depaoli, Sarah; Clifton, James P.; Cobb, Patrice R. – Journal of Educational and Behavioral Statistics, 2016
A review of the software Just Another Gibbs Sampler (JAGS) is provided. We cover aspects related to history and development and the elements a user needs to know to get started with the program, including (a) definition of the data, (b) definition of the model, (c) compilation of the model, and (d) initialization of the model. An example using a…
Descriptors: Monte Carlo Methods, Markov Processes, Computer Software, Models
Xi, Nuo; Browne, Michael W. – Journal of Educational and Behavioral Statistics, 2014
A promising "underlying bivariate normal" approach was proposed by Jöreskog and Moustaki for use in the factor analysis of ordinal data. This was a limited information approach that involved the maximization of a composite likelihood function. Its advantage over full-information maximum likelihood was that very much less computation was…
Descriptors: Factor Analysis, Maximum Likelihood Statistics, Data, Computation