Patz and Junker (1999) describe a general Markov chain Monte Carlo (MCMC) strategy, based on Metropolis-Hastings sampling, for Bayesian inference in complex item response theory (IRT) settings. They demonstrate the basic methodology using the two-parameter logistic (2PL) model. In this paper we...

Australia’s statistics are of a high quality. Based on the review of its statistical practices, a set of recommendations is presented designed to increase its adherence to internationally accepted statistical practices. The aim of the review is to enhance the usefulness of...

Questions about monetary variables (such as income, wealth or savings) are key components of questionnaires on household finances. However, missing information on such sensitive topics is a well-known phenomenon which can seriously bias any inference based only on complete-case analysis. Many...

This report on the Observance of Standards and Codes on Data Module for Indonesia highlights that the Indonesian statistical system is undergoing fundamental transition. The statistical agencies are dealing with important challenges. They are at various stages of adopting and implementing...

Multiple Imputation describes a strategy for analyzing incomplete data that accounts for uncertainty in the missing data by replacing (imputing) each missing value by several ‘candidates’. The actual implementation of any Multiple Imputation method is typically computationally expensive...