Goodness-of-Fit Statistics for General Linear Regression Equations in the Presence of Replicated Responses

Goodness-of-fit statistics for general multiple-linear-regression equations are reviewed for the case of replicated responses.A modification of the coefficient of determination is recommended.This statistic has 1.0 as its achievable upper bound and has the coefficient of determination as a special case.It indicates more effectively how close a general-linear-regression equation is relative to the best possible one and is particularly useful when the purpose is to ascertain whether higher-order terms of a given set of explanatory variables are required.Other goodness-of-fit statistics that take into account the variation within replicated responses are reviewed.An illustration example is presented.