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Adjusting for Random Measurement Error and Misclassification Using SIMEX

Training materials for short course ‘Adjustment Methods for Data Quality Problems: Missing Data, Measurement Error, and Misclassification.’

Published onDec 22, 2023
Adjusting for Random Measurement Error and Misclassification Using SIMEX
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Abstract

In this workshop we will practice using SIMEX (Cook & Stefanski, 1994) and MC-SIMEX (Küchenhoff et al., 2006) to adjust for different types of random measurement error and misclassification. To do so we will employ the package simex (Lederer et al., 2019), and a couple of datasets derived from the Cyber Security Breaches Survey and the Magistrates Court Sentencing Survey. This is the second practical exercise from day 2 of the short course ‘Adjustment Methods for Data Quality Problems: Missing Data, Measurement Error, and Misclassification.’ You can download the associated lecture slides and data here: https://github.com/jmpinasanchez/measurement

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