Regressions are commonly misinterpreted

David C. Hoaglin ()

Stata Journal, 2016, vol. 16, issue 1, 5-22

Abstract: Much literature misinterprets results of fitting multivariable models for linear regression, logistic regression, and other generalized linear models, as well as for survival, longitudinal, and hierarchical regressions. For the leading case of multiple regression, regression coefficients can be accurately interpreted via the added-variable plot. However, a common interpretation does not reflect the way regression methods actually work. Additional support for the correct in- terpretation comes from examining regression coefficients in multivariate normal distributions and from the geometry of least squares. To properly implement mul- tivariable models, one must be cautious when calculating predictions that average over other variables, as in the Stata command margins. Copyright 2016 by StataCorp LP.

Keywords: regression models; added-variable plot; multivariate normal distribution; geometry of least squares; margins command (search for similar items in EconPapers)
Date: 2016
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