Resources

Publications of TG 4

Freedman LS, Kipnis V on behalf of STRATOS TG4 (2018). STRengthening Analytical Thinking for Observational Studies (STRATOS): Introducing the Measurement Error and Misclassification Topic Group (TG4). Biometric Bulletin; 35(1):10. Link

Shaw PA, Deffner, V, Keogh RH, Tooze JA, Dodd KW, Küchenhoff H, Kipnis V, Freedman LS, Measurement Error and Misclassification Topic Group (TG4) of the STRATOS Initiative (2018). Epidemiologic analyses with error-prone exposures: Review of current practice and recommendations. Annals of Epidemiology. Link

Keogh R, Shaw P, Gustafson P, Carroll R, Deffner V, Dodd K, Küchenhoff H, Tooze J, Wallace M, Kipnis V, Freedman L (2020). STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 1 – basic theory, validation studies and simple methods of adjustment. Statistics in Medicine. Link

Shaw P, Gustafson P, Carroll R, Deffner V, Keogh R, Tooze J, Kipnis V, Wallace M, Küchenhoff H, Freedman L (2020). STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 2 – sample size, more complex methods of adjustment and advanced topics. Statistics in Medicine. Link

Wallace M (2020). Analysis in an imperfect world. Significance; 17.1:14-19. Link

Further information

Weblectures 

Measurement Error: Impact on Nutrition Research and Adjustment for its Effects (Biometry Research Group, DCP, National Cancer Institute)

Related publications

Brakenhoff TB, Mitroiu M, Keogh RH, Moons KGM, Groenwold RHH, van Smeden M (2018). Measurement error is often neglected in medical literature: a systematic review. Journal of Clinical Epidemiology; 98: 89-97. Link 

Pangratz E (2017). Measurement Error and Study Design in Air Pollution Epidemiology. Impacts and Recommendations. Bachelor thesis, Ludwig-Maximilians-Universität München, Department of Statistics. Link

van Smeden M, Lash TL, Groenwold RHH (2020). Reflection on modern methods: five myths about measurement error in epidemiologic research. International Journal of Epidemiology; 49(1): 338–347. LinkÂ