Methods of fitting straight lines where both variables are subject to measurement error

Gillard, Jonathan William ORCID: https://orcid.org/0000-0001-9166-298X and Iles, Terence Crossley 2009. Methods of fitting straight lines where both variables are subject to measurement error. Current Clinical Pharmacology 4 (3) , pp. 164-171. 10.2174/157488409789375302

Full text not available from this repository.

Abstract

In this paper errors in variables methods for fitting straight lines to data are reviewed. In these methods the x and y variables are both assumed to be subject to measurement error and not, as in simple least squares linear regression, just one of them. The methods are described in a unified context using the statistical principle of the method of moments. Guidance is given on the choice of an appropriate method of estimating the slope and intercept of the fitted line. Formulas for the approximate standard errors of the estimators are provided in a technical appendix. A numerical example from biochemical studies is included to illustrate the methodology.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics
Subjects:	Q Science > QA Mathematics
Uncontrolled Keywords:	Errors in variables regression; measurement error; method of moments estimation
Publisher:	Bentham Science Publishers
ISSN:	1574-8847
Last Modified:	19 Oct 2022 08:47
URI:	https://orca.cardiff.ac.uk/id/eprint/19043

Citation Data

Cited 7 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item