Impact of additive covariate error on linear model

AbstractWe consider effect of additive covariate error on linear model in observational (radiation epidemiology) study for exposure risk. Additive dose error affects dose-response shape under general linear regression settings covering identity-link GLM type models and linear excess-relative-risk grouped-Poisson models. Under independent error, dose distribution that log of dose density is up to quadratic polynomial on an interval (the log-quadratic density condition), normal, exponential, and uniform distributions, is the condition for linear regression calibration. Violation of the condition can result low-dose-high-sensitivity model from linear no-threshold (LNT) model by the dose error. Power density is also considered. A published example is given.