Modeling Nonlinearity and Interaction in Regression Analysis Using Spline Variables
- Roger A. Wojtkiewicz - Ball State University, USA
"Spline variables and their interactions play a crucial role in the field of social science. This book offers a comprehensive and detailed exploration of this method, providing valuable insights and information for researchers in the field."
--Man-Kit Lei, The University of Georgia
This volume addresses the issue of linear constraints in regression modeling. Author Roger A. Wojtkiewicz uses the method of knotted spline variables (also known as piecewise linear regression) and a new method involving group spline variables to model nonlinearity in a variety of situations. Using spline variables to model nonlinearity allows researchers to specify unrestricted models for models that involve interval variables, allowing for greater flexibility in modeling any possible interaction.
Spline variables and their interactions play a crucial role in the field of social science. This book offers a comprehensive and detailed exploration of this method, providing valuable insights and information for researchers in the field.
In regression analyses, most books on interactions involving an interval variable knowingly or unknowingly often assume that the interaction effect is linear and the same for all participants in each of the created groups to explain the interaction effect. However, this may not always be the case. Splines, that are widely used to model non-linearity in regression models have not been extensively used to explain interaction effects. This easy-to-read book by Dr. Roger Wojtkiewicz, which has a strong conceptual framework, provides empirical evidence illustrating the use of knotted splines and group splines in modeling nonlinearity in interaction models. This book will be a valuable addition to the library of any analyst with at least intermediate knowledge of regression models who is interested in explaining regression effects across groups using interactions.
