Abstract
周舒冬,郜艳晖,李丽霞,张敏,杨翌,陈跃.稳健Poisson和log.binomial的GEE模型应用于非独立数据的研究[J].Chinese journal of Epidemiology,2014,35(4):449-452
稳健Poisson和log.binomial的GEE模型应用于非独立数据的研究
A simalation case study under the use of robust Poisson and log.binomial model with generalized estimating equation models regarding non-independent data
Received:October 18, 2013  
DOI:10.3760/cma.j.issn.0254-6450.2014.04.024
KeyWord: 稳健Poisson回归  log.binomial模型  非独立  广义估计方程
English Key Word: Robust Poisson regression  Log-binomial model  Non-independent  Generalized estimating equation
FundProject:广东省自然科学基金(10151022401000018)
Author NameAffiliationE-mail
Zhou Shudon Guangdong Key Laboratory of Molecular Epidemiology, Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou 5100310, China  
Gao Yanhui Guangdong Key Laboratory of Molecular Epidemiology, Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou 5100310, China gao_yanhui@.163.com 
Li Lixia Guangdong Key Laboratory of Molecular Epidemiology, Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou 5100310, China  
Zhang Min Guangdong Key Laboratory of Molecular Epidemiology, Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou 5100310, China  
Yang Yi Guangdong Key Laboratory of Molecular Epidemiology, Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou 5100310, China  
Chen Yue Department of Epidemiology and Community Medicine, University of Ottawa, Canada  
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Abstract:
      探讨流行病学资料中非独立数据的RR/患病率比(PR)的合适估计方法 。采用计算机模拟实验和实例分析观察稳健Poisson.GEE和log-binomial.GEE模型的适用性并进行比较。结果 表明log.binomial-GEE模型与稳健Poisson-GEE模型的收敛率基本均为100%,两模型估计各参数的平均值均与真值接近;在类内聚集性变小或类别数增加时,两模型估计各参数的95%CI覆盖率均有所提高;稳健Poisson.GEE模型对参数估计的稳健性较好,应用到实例时可正确评价暴露对结局的影响。稳健Poisson和log.binomial的GEE模型很少存在收敛问题,且有较高的准确率,可用于流行病学资料中非独立数据的RR/PR值估计。
English Abstract:
      To explore the appropriate method in estimating relative risk(RR)/prevalence ratio(PR)related to non·independent datasets.The simulation datasets generated by computer and case study were analyzed by two generalized estimating equation(GEE)models to investigate and compare the related applicability.Both convergence effects of log·binomial·-GEE model and Robust Poisson.GEE model were almost 100%.The estimation Results of the two GEE models were both closer to the true value.95%Cl coverage of the two GEE models increased along with the reduction of class aggregation or the increase of the number of categories.Robust-Poisson-GEE model seemed to be more stable and steady than the log-binomial-GEE.The two GEE models could correctly evaluate the effects of exposure on the outcome in the case study.Rarely,there appeared problems on convergence of Robust Poisson or log-binomial-GEE model,and the accuracy was high.Both models could be used to estimate the RRiPR on non-independent epidemiological data.
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