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Simulation & Estimation

All-access Pass
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.
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
Module 42: Simulation Studies in Psychometrics
In this print module, Dr. Richard A. Feinberg and Dr. Jonathan D. Rubright provide a comprehensive introduction to the topic of simulation studies in psychometrics using R that can be easily understood by measurement specialists at all levels of training and experience. Keywords: bias, experimental design, mean absolute difference, MAD, mean squared error, MSE, root mean squared error, RMSE, psychometrics, R, research design, simulation study, standard error