Abstract
When dealing with the association between some random variable and two covariates, extensive experience with smoothers indicates that often a linear model poorly reflects the nature of the association. A simple approach via quantile grids that reflects the nature of the association is given. The two main goals are to illustrate this approach can make a practical difference, and to describe R functions for applying it. Included are comments on dealing with more than two covariates.
DOI
10.22237/jmasm/1556670120
Erratum
A previous version of this article had a character encoding error with epsilon in equation (1). This has now been corrected.
Recommended Citation
Wilcox, R. (2019). Regression when there are two covariates: Some practical reasons for considering quantile grids. Journal of Modern Applied Statistical Methods, 18(1), eP3227. doi: 10.22237/jmasm/1556670120
Included in
Applied Statistics Commons, Social and Behavioral Sciences Commons, Statistical Theory Commons
