Modelling measurement errors and category misclassifications in multilevel models

H Goldstein, D Kounali, Anthony Robinson

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)

Abstract

Models are developed to adjust for measurement errors in normally distributed predictor and response variables and categorical predictors with misclassification errors. The models allow for a hierarchical data structure and for correlations among the errors and misclassifications. Markov Chain Monte Carlo (MCMC) estimation is used and implemented in a set of MATLAB macros.
Original languageEnglish
Pages (from-to)243-261
Number of pages19
JournalStatistical Modelling
Volume8
Issue number3
DOIs
Publication statusPublished - Sep 2008

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