Impact of additive covariate error on linear model

Eiji Nakashima

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 22, 5517-5529

Abstract: We 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.

Date: 2019
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DOI: 10.1080/03610926.2018.1515361

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