Abstract
This expository note discusses the problem of fitting a straight line when both variables are subject to error. A brief review of the literature is undertaken, and one fitting method, the geometric mean functional relationship, is spotlighted and illustrated with two sets of example data. The emphasis is on providing practical advice. All methods have drawbacks, but the geometric mean functional relationship method appears to provide a sensible course of action in many practical problems, and could benefit from further investigation.
Keywords
functional relationship
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Draper, Norman R.
(1991).
"STRAIGHT LINE REGRESSION WHEN BOTH VARIABLES ARE SUBJECT TO ERROR,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1414
STRAIGHT LINE REGRESSION WHEN BOTH VARIABLES ARE SUBJECT TO ERROR
This expository note discusses the problem of fitting a straight line when both variables are subject to error. A brief review of the literature is undertaken, and one fitting method, the geometric mean functional relationship, is spotlighted and illustrated with two sets of example data. The emphasis is on providing practical advice. All methods have drawbacks, but the geometric mean functional relationship method appears to provide a sensible course of action in many practical problems, and could benefit from further investigation.
