Horton N J, Bebchuk J D, Jones C L, Lipsitz S R, Catalano P J, Zahner G E, Fitzmaurice G M
Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA.
Stat Med. 1999 Jan 30;18(2):213-22. doi: 10.1002/(sici)1097-0258(19990130)18:2<213::aid-sim999>3.0.co;2-e.
Suppose we use generalized estimating equations to estimate a marginal regression model for repeated binary observations. There are no established summary statistics available for assessing the adequacy of the fitted model. In this paper we propose a goodness-of-fit test statistic which has an approximate chi-squared distribution when we have specified the model correctly. The proposed statistic can be viewed as an extension of the Hosmer and Lemeshow goodness-of-fit statistic for ordinary logistic regression to marginal regression models for repeated binary responses. We illustrate the methods using data from a study of mental health service utilization by children. The repeated responses are a set of binary measures of service use. We fit a marginal logistic regression model to the data using generalized estimating equations, and we apply the proposed goodness-of-fit statistic to assess the adequacy of the fitted model.
假设我们使用广义估计方程来估计重复二元观测的边际回归模型。目前尚无既定的汇总统计量可用于评估拟合模型的充分性。在本文中,我们提出了一种拟合优度检验统计量,当我们正确指定模型时,该统计量具有近似的卡方分布。所提出的统计量可视为普通逻辑回归的Hosmer和Lemeshow拟合优度统计量到重复二元响应的边际回归模型的扩展。我们使用一项关于儿童心理健康服务利用情况研究的数据来说明这些方法。重复响应是一组关于服务使用的二元测量。我们使用广义估计方程对数据拟合边际逻辑回归模型,并应用所提出的拟合优度统计量来评估拟合模型的充分性。