抄録
In binary regression models we are interested in not only the parameter estimates and significance of explanatory variables, but also the degree to which variation in the response variable can be explained by explanatory variables. In this paper, we compare the behavior of proposed measures of explained variation for binary regression models through several case studies and indicate which measures should be accepted in practice. Furthermore, the importance of distinguishing measures of explained variation and goodness-of-fit is discussed. In conclusion, we recommend routine evaluation of the measures of explained variation in binary regression together with an exhaustive model which allows us to test the adequacy of simpler models such as the logistic model.
