Craiu Radu V, Duchesne Thierry, Fortin Daniel
Department of Statistics, University of Toronto, 100 St. George Street, Toronto, Ontario, M5S 3G3, Canada.
Biom J. 2008 Feb;50(1):97-109. doi: 10.1002/bimj.200610379.
This paper considers inference methods for case-control logistic regression in longitudinal setups. The motivation is provided by an analysis of plains bison spatial location as a function of habitat heterogeneity. The sampling is done according to a longitudinal matched case-control design in which, at certain time points, exactly one case, the actual location of an animal, is matched to a number of controls, the alternative locations that could have been reached. We develop inference methods for the conditional logistic regression model in this setup, which can be formulated within a generalized estimating equation (GEE) framework. This permits the use of statistical techniques developed for GEE-based inference, such as robust variance estimators and model selection criteria adapted for non-independent data. The performance of the methods is investigated in a simulation study and illustrated with the bison data analysis.
本文考虑纵向设置下病例对照逻辑回归的推断方法。对平原野牛空间位置作为栖息地异质性函数的分析提供了动机。抽样是根据纵向匹配病例对照设计进行的，在某些时间点，恰好一个病例（动物的实际位置）与多个对照（可能到达的替代位置）相匹配。我们在此设置下为条件逻辑回归模型开发推断方法，该模型可在广义估计方程（GEE）框架内构建。这允许使用为基于GEE的推断开发的统计技术，如稳健方差估计器和适用于非独立数据的模型选择标准。在模拟研究中研究了这些方法的性能，并通过野牛数据分析进行了说明。
