Goodness of fit tests for the multiple logistic regression model

作者：David W. Hosmer, Stanley Lemesbow · 发表于：Communication in Statistics- Theory and Methods · 年份：1980 · DOI：10.1080/03610928008827941 · 被引用次数：1886 · 研究领域：Advanced Statistical Methods and Models、Statistical Methods and Bayesian Inference、Bayesian Methods and Mixture Models

Several test statistics are proposed for the purpose of assessing the goodness of fit of the multiple logistic regression model. The test statistics are obtained by applying a chi-square test for a contingency table in which the expected frequencies are determined using two different grouping strategies and two different sets of distributional assumptions. The null distributions of these statistics are examined by applying the theory for chi-square tests of Moore Spruill (1975) and through computer simulations. All statistics are shown to have a chi-square distribution or a distribution which can be well approximated by a chi-square. The degrees of freedom are shown to depend on the particular statistic and the distributional assumptions. The power of each of the proposed statistics is examined for the normal, linear, and exponential alternative models using computer simulations.