Curvilinear Estimation (20 Patients)

Abstract

The general principle of regression analysis is that the best fit line/exponential-curve/curvilinear-curve etc. is calculated, i.e., the one with the shortest distances to the data, and that it is, subsequently, tested how far the data are from the curve. A significant correlation between the y (outcome data) and the x (exposure data) means that the data are closer to the model than will happen purely by chance. The level of significance is usually tested, simply, with t-tests or analysis of variance. The simplest regression model is a linear model.