Teaching about measurement error

Tutorials and tools for learning about handling measurement error in the statistical analysis

Toolkit for measurement error correction

  • Toolkit for measurement error correction using repeated measurements
  • Classical, systematic, heteroscedastic and differential measurement error
  • Correction methods: regression calibration, moment reconstruction, multiple imputation
  • Error in continuous exposures and categorized continuous exposures


  • User-frendly app for interactive exploration of the impacts of measurement error and misclassification
  • Linear regression models
  • Classical, linear and Berkson error in categorical and continuous covariates
  • Based on the STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology

Other tools

  • Shiny app: Impact of measurement error in a predictor (Link)
  • Shiny app: Classical measurement error in linear, logit and Poisson regression (Link)