TY - JOUR
T1 - The performance of functional methods for correcting non-Gaussian measurement error within Poisson regression
T2 - Corrected excess risk of lung cancer mortality in relation to radon exposure among French uranium miners
AU - Allodji, Rodrigue S.
AU - Thiébaut, Anne C.M.
AU - Leuraud, Klervi
AU - Rage, Estelle
AU - Henry, Stéphane
AU - Laurier, Dominique
AU - Bénichou, Jacques
PY - 2012/12/30
Y1 - 2012/12/30
N2 - A broad variety of methods for measurement error (ME) correction have been developed, but these methods have rarely been applied possibly because their ability to correct ME is poorly understood. We carried out a simulation study to assess the performance of three error-correction methods: two variants of regression calibration (the substitution method and the estimation calibration method) and the simulation extrapolation (SIMEX) method. Features of the simulated cohorts were borrowed from the French Uranium Miners' Cohort in which exposure to radon had been documented from 1946 to 1999. In the absence of ME correction, we observed a severe attenuation of the true effect of radon exposure, with a negative relative bias of the order of 60% on the excess relative risk of lung cancer death. In the main scenario considered, that is, when ME characteristics previously determined as most plausible from the French Uranium Miners' Cohort were used both to generate exposure data and to correct for ME at the analysis stage, all three error-correction methods showed a noticeable but partial reduction of the attenuation bias, with a slight advantage for the SIMEX method. However, the performance of the three correction methods highly depended on the accurate determination of the characteristics of ME. In particular, we encountered severe overestimation in some scenarios with the SIMEX method, and we observed lack of correction with the three methods in some other scenarios. For illustration, we also applied and compared the proposed methods on the real data set from the French Uranium Miners' Cohort study.
AB - A broad variety of methods for measurement error (ME) correction have been developed, but these methods have rarely been applied possibly because their ability to correct ME is poorly understood. We carried out a simulation study to assess the performance of three error-correction methods: two variants of regression calibration (the substitution method and the estimation calibration method) and the simulation extrapolation (SIMEX) method. Features of the simulated cohorts were borrowed from the French Uranium Miners' Cohort in which exposure to radon had been documented from 1946 to 1999. In the absence of ME correction, we observed a severe attenuation of the true effect of radon exposure, with a negative relative bias of the order of 60% on the excess relative risk of lung cancer death. In the main scenario considered, that is, when ME characteristics previously determined as most plausible from the French Uranium Miners' Cohort were used both to generate exposure data and to correct for ME at the analysis stage, all three error-correction methods showed a noticeable but partial reduction of the attenuation bias, with a slight advantage for the SIMEX method. However, the performance of the three correction methods highly depended on the accurate determination of the characteristics of ME. In particular, we encountered severe overestimation in some scenarios with the SIMEX method, and we observed lack of correction with the three methods in some other scenarios. For illustration, we also applied and compared the proposed methods on the real data set from the French Uranium Miners' Cohort study.
KW - Error-correction methods
KW - Lung cancer risk
KW - Measurement error
KW - Poisson regression
KW - Uranium miners exposed to radon
UR - http://www.scopus.com/inward/record.url?scp=84870898140&partnerID=8YFLogxK
U2 - 10.1002/sim.5618
DO - 10.1002/sim.5618
M3 - Article
C2 - 22996087
AN - SCOPUS:84870898140
SN - 0277-6715
VL - 31
SP - 4428
EP - 4443
JO - Statistics in Medicine
JF - Statistics in Medicine
IS - 30
ER -