Citation

Masiuk SV, Shklyar SV, Kukush AG, Carroll RJ, Kovgan LN, Likhtarov IA. Biostatistics 2016; 17(3): 422-436.

Affiliation

State Institution "National Research Center for Radiation Medicine of the National Academy of Medical Sciences of Ukraine", Melnykova str., 53, Kyiv, 04050, Ukraine; Ukrainian Radiation Protection Institute, Melnykova str., 53, Kyiv, 04050, Ukraine.

Copyright

(Copyright © 2016, Oxford University Press)

DOI

10.1093/biostatistics/kxv052

PMID

26795191

Abstract

In this paper, the influence of measurement errors in exposure doses in a regression model with binary response is studied. Recently, it has been recognized that uncertainty in exposure dose is characterized by errors of two types: classical additive errors and Berkson multiplicative errors. The combination of classical additive and Berkson multiplicative errors has not been considered in the literature previously. In a simulation study based on data from radio-epidemiological research of thyroid cancer in Ukraine caused by the Chornobyl accident, it is shown that ignoring measurement errors in doses leads to overestimation of background prevalence and underestimation of excess relative risk. In the work, several methods to reduce these biases are proposed. They are new regression calibration, an additive version of efficient SIMEX, and novel corrected score methods.

Language: en