Straight Line Regression When Both Variables Are Subject to Error

This is the authors' abstract. We don't add key points for this paper.

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.