A goodness-of-fit test for logistic regression models based on case-control data

• 成果类型: Article
• 署名作者: Qin, J; Zhang, B
• 署名单位: University System of Ohio; University of Toledo
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/84.3.609
• 发表日期: 1997
• 页码: 609618
• 关键词: empirical distributions; likelihood; BIAS

摘要

We test the logistic regression assumption under a case-control sampling plan. After reparameterisation, the assumed logistic regression model is equivalent to a two-sample semiparametric model in which the log ratio of two density functions is linear in data. By identifying this model with a biased sampling model, we propose a Kolmogorov-Smirnov-type statistic to test the validity of the logistic link function. Moreover, we point out that this test statistic can also be used in mixture sampling. We present a bootstrap procedure along with some results on simulation and on analysis of two real datasets.