Author(s)

Michael Brimacombe

Department of Biostatistics, KUMC, Kansas City, KS, USA.

The effects of centering response and explanatory variables as a way of simplifying fitted linear models in the presence of correlation are reviewed and extended to include nonlinear models, common in many biological and economic applications. In a nonlinear model, the use of a local approximation can modify the effect of centering. Even in the presence of uncorrelated explanatory variables, centering may affect linear approximations and related test statistics. An approach to assessing this effect in relation to intrinsic curvature is developed and applied. Mis-specification bias of linear versus nonlinear models also reflects this centering effect.

Nonlinear Regression, Centering Data, Model Mis-Specification, Bias, Curvature

Brimacombe, M. (2016) Local Curvature and Centering Effects in Nonlinear Regression Models. Open Journal of Statistics, 6, 76-84. doi: 10.4236/ojs.2016.61010.