Backpropagation and regression: comparative utility for neuropsychologists.

The aim of this research was to compare the data analytic applicability of a backpropagated neural network with that of regression analysis. Thirty individuals between the ages of 64 and 86 (Mean age = 73.6; Mean years education = 15.4; % women = 50) participated in a study designed to validate a new test of spatial ability administered in virtual reality. As part of this project a standard neuropsychological battery was administered. Results from the multiple regression model R(2) = .21, p < .28; Standard Error = 18.01) were compared with those of a backpropagated ANN (R(2) = .39, p < .02; Standard Error = 13.07). This 18% increase in prediction of a common neuropsychological problem demonstrated that an ANN has the potential to outperform a regression.