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Impact of additive covariate error on linear model

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  • Eiji Nakashima

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.

Suggested Citation

  • Eiji Nakashima, 2019. "Impact of additive covariate error on linear model," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(22), pages 5517-5529, November.
    • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:22:p:5517-5529
    DOI: 10.1080/03610926.2018.1515361
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