On association in regression: the coefficient of determination revisited

Abstract

Universal coefficients of determination are investigated which quantify the strength of the relation between a vector of dependent variables Y and a vector of independent covariates X. They are defined as measures of dependence between Y and X through θ(x), with θ(x) parameterizing the conditional distribution of Y given X = x. If θ(x) involves unknown coefficients γ the definition is conditional on γ, and in practice γ, respectively the coefficient of determination has to be estimated. The estimates of quantities we propose generalize R 2 in classical linear regression and are also related to other definitions previously suggested. Our definitions apply to generalized regression models with arbitrary link functions as well as multivariate and nonparametric regression. The definition and use of the proposed coefficients of determination is illustrated for several regression problems with simulated and real data sets.