ACCESS IS FREE!
Quickly create a new user account for the Elevate learning management system (this website) to access any modules.
You do NOT have to be an NCME member to do this!
This provides immediate access to ALL print and digital modules in the portal by "registering" you for each and displaying all modules as a single collection as part of this pass.
All-access Pass (PRINT ONLY)
This provides access to a ZIP folder with all 45 previously published print modules.
Digital Module 11: Bayesian Psychometrics
In this digital ITEMS module, Dr. Roy Levy discusses how Bayesian inference is a mechanism for reasoning in probability-modeling framework, describes how this plays out in a normal distribution model and unidimensional item response theory (IRT) models, and illustrates these steps using the JAGS software and R. Keywords: Bayesian psychometrics, Bayes theorem, dichotomous data, item response theory (IRT), JAGS, Markov-chain Monte Carlo (MCMC) estimation, normal distribution, R, unidimensional models
Digital Module 06: Posterior Predictive Model Checking
In this digital ITEMS module, Dr. Allison Ames and Aaron Myers discuss the most common Bayesian approach to model-data fit evaluation, which is called Posterior Predictive Model Checking (PPMC), for simple linear regression and item response theory models. Keywords: Bayesian inference, simple linear regression, item response theory, IRT, model fit, posterior predictive model checking, PPMC, Bayes theorem, Yen’s Q3, item fit
Module 27: Markov Chain Monte Carlo Methods for Item Response Theory Models
In this print module, Dr. Jee-Seon Kim and Dr. Daniel M. Bolt provide an introduction to Markov chain Monte Carlo (MCMC) estimation for item response (IRT) models and illustrate these ideas with a two-parameter logistic (2PL) model in the software program Winbugs. Keywords: Bayesian estimation, goodness-of-fit, item response theory, IRT, Markov chain Monte Carlo, MCMC, model comparison, two-parameter model, 2PL, Winbugs
|Access Date||Quiz Result||Score||Actions|
André A. Rupp (Editor, 2016-2021)
Phone: (443) 538-7794