Measurement error correction for the cumulative average model in the survival analysis of nutritional data: application to Nurses' Health Study.
The use of the cumulative average model to investigate the association between disease incidence and repeated measurements of exposures in medical follow-up studies can be dated back to the 1960s (Kahn and Dawber, J Chron Dis 19:611-620, 1966). This model takes advantage of all prior data and thus should provide a statistically more powerful test of disease-exposure associations. Measurement error in covariates is common for medical follow-up studies. Many methods have been proposed to correct for measurement error. To the best of our knowledge, no methods have been proposed yet to correct for measurement error in the cumulative average model. In this article, we propose a regression calibration approach to correct relative risk estimates for measurement error. The approach is illustrated with data from the Nurses' Health Study relating incident breast cancer between 1980 and 2002 to time-dependent measures of calorie-adjusted saturated fat intake, controlling for total caloric intake, alcohol intake, and baseline age.
Qiu
Weiliang
W
Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Rosner
Bernard
B
D015982:Bias; D001943:Breast Neoplasms / Q000453:epidemiology*; D003198:Computer Simulation; D004041:Dietary Fats / Q000008:administration & dosage*; D005260:Female; D006801:Humans; D015994:Incidence; D015233:Models, Statistical
D004041:Dietary Fats