Adaptive Modeling: An Approach for Incorporating Nonlinearity in Regression Analyses

Abstract
Although regression relationships commonly are treated as linear, this often is not the case. An adaptive approach is described for identifying nonlinear relationships based on power transforms of predictor (or independent) variables and for assessing whether or not relationships are distinctly nonlinear. It is also possible to model adaptively both means and variances of continuous outcome (or dependent) variables and to adaptively power transform positive‐valued continuous outcomes, along with their predictors. Example analyses are provided of data from parents in a nursing study on emotional‐health‐related quality of life for childhood brain tumor survivors as a function of the effort to manage the survivors' condition. These analyses demonstrate that relationships, including moderation relationships, can be distinctly nonlinear, that conclusions about means can be affected by accounting for non‐constant variances, and that outcome transformation along with predictor transformation can provide distinct improvements and can resolve skewness problems.© 2017 Wiley Periodicals, Inc.

Source: Research in Nursing and Health - January 31, 2017 Category: Nursing Authors: George J. Knafl, Lamia P. Barakat, Alexandra L. Hanlon, Thomas Hardie, Kathleen A. Knafl, Yimei Li, Janet A. Deatrick Tags: Research Article Source Type: research