Goodman Melody S, Li Yi
Division of Public Health Sciences, Department of Surgery, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.
J Biom Biostat. 2012 Mar 1;3(2). doi: 10.4172/2155-6180.1000136.
The use of conditional logistic regression models to analyze matched case-control data has become standard in statistical analysis. However, methods to test the fit of these models has primarily focused on influential observations and the presence of outliers, while little attention has been given to the functional form of the covariates. In this paper we present methods to test the functional form of the covariates in the conditional logistic regression model, these methods are based on nonparametric smoothers. We assess the performance of the proposed methods via simulation studies and illustrate an example of their use on data from a community based intervention.
使用条件逻辑回归模型来分析匹配的病例对照数据已成为统计分析中的标准方法。然而，检验这些模型拟合优度的方法主要集中在有影响的观测值和异常值的存在上，而对协变量的函数形式关注较少。在本文中，我们提出了检验条件逻辑回归模型中协变量函数形式的方法，这些方法基于非参数平滑器。我们通过模拟研究评估了所提出方法的性能，并举例说明了它们在基于社区干预的数据中的应用。
