title: Simulation-based Bayesian inference for latent traits of item response models: Introduction to the ltbayes package for R.
abstract: This paper introduces the ltbayes package for R. This package includes a suite of functions for investigating the posterior distribution of latent traits of item response models. These include functions for simulating realizations from the posterior distribution, profiling the posterior density or likelihood function, calculation of posterior modes or means, Fisher information functions and observed information, and profile likelihood confidence intervals. Inferences can be based on individual response patterns or sets of response patterns such as sum scores. Functions are included for several common binary and polytomous item response models, but the package can also be used with user-specified models. This paper introduces some background and motivation for the package, and includes several detailed examples of its use.
authors.affiliation: Department of Statistical Science, University of Idaho, 875 Perimeter Drive MS 1104, Moscow, ID, 83844-1104, USA. trjohns@uidaho.edu.
authors.forename: Timothy R
authors.initials: TR
authors.lastname: Johnson
authors.affiliation: Department of Management, Information Systems, and Entrepreneurship, Washington State University, Pullman, WA, 99164-4736, USA.
authors.forename: Kristine M
authors.initials: KM
authors.lastname: Kuhn
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D003198:Computer Simulation; D016001:Confidence Intervals; D006801:Humans; D016013:Likelihood Functions; D008960:Models, Psychological; D015233:Models, Statistical; D012984:Software
keywords: Bayesian statistics; Item response theory; R