{"title":"Modifications of QIC and CIC for Selecting a Working Correlation Structure in the Generalized Estimating Equation Method","authors":"M. Gosho, C. Hamada, I. Yoshimura","doi":"10.5691/JJB.32.1","DOIUrl":null,"url":null,"abstract":"The generalized estimating equation (GEE) method is a popular method for analyzing longitudinal data. An inappropriate specification of the working correlation structure reduces the effciency of the GEE estimation. Pan (2001a) and Hin and Wang (2009) proposed a quasi-likelihood under the independence model criterion (QIC) and a correlation information criterion (CIC) for selecting a proper working correlation structure, respectively. In this study, we proposed modifications to the QIC and CIC using the variance estimators of the GEE with improved small-sample properties. In a simulation study, the performance of the modified QIC and CIC was better than that of the original QIC and CIC. The modified methods were illustrated using the data for an air pollution study.","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Japanese journal of biometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5691/JJB.32.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The generalized estimating equation (GEE) method is a popular method for analyzing longitudinal data. An inappropriate specification of the working correlation structure reduces the effciency of the GEE estimation. Pan (2001a) and Hin and Wang (2009) proposed a quasi-likelihood under the independence model criterion (QIC) and a correlation information criterion (CIC) for selecting a proper working correlation structure, respectively. In this study, we proposed modifications to the QIC and CIC using the variance estimators of the GEE with improved small-sample properties. In a simulation study, the performance of the modified QIC and CIC was better than that of the original QIC and CIC. The modified methods were illustrated using the data for an air pollution study.
广义估计方程(GEE)法是一种常用的纵向数据分析方法。工作相关结构的不适当规范降低了GEE估计的效率。Pan (2001a)和Hin and Wang(2009)分别提出了独立模型准则下的准似然准则(QIC)和相关信息准则(CIC)来选择合适的工作关联结构。在本研究中，我们使用改进小样本性质的GEE方差估计器对QIC和CIC进行了修改。在仿真研究中，改进后的QIC和CIC的性能都优于原QIC和CIC。用一项空气污染研究的数据说明了改进的方法。
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
