文章摘要
柏建岭,荀鹏程,赵杨,于浩,沈洪兵,陈峰,魏庆义.不完全病例对照研究中对照组部分基因信息缺失基因-环境交互作用的估计[J].中华流行病学杂志,2007,28(8):806-809
不完全病例对照研究中对照组部分基因信息缺失基因-环境交互作用的估计
Estimation of gene-environment interaction regarding partial case-control study with missing data on gene information of the controls
投稿时间:2007-01-05  修订日期:2007-08-10
DOI:
中文关键词: 不完全病例对照研究;基因-环境交互作用;缺失数据
英文关键词: Partial case-control study;Gene-environment interaction;Missing data
基金项目:国家自然科学基金资助项目(30571619);国家重点基础研究发展计划(973)资助项目(2002CB512910);江苏省高校自然科学基金重点资助项目(04KJB310081)
作者单位E-mail
柏建岭 南京医科大学公共卫生学院流行病与卫生统计学系, 210029  
荀鹏程 南京医科大学公共卫生学院流行病与卫生统计学系, 210029  
赵杨 南京医科大学公共卫生学院流行病与卫生统计学系, 210029  
于浩 南京医科大学公共卫生学院流行病与卫生统计学系, 210029  
沈洪兵 南京医科大学公共卫生学院流行病与卫生统计学系, 210029  
陈峰 南京医科大学公共卫生学院流行病与卫生统计学系, 210029 dr.chenfeng@163.com 
魏庆义 Department of Epidemiology,University of Texas M.D.Anderson Cancer Center,Houston,TX,USA  
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中文摘要:
      目的 探讨不完全病例对照研究中对照组基因信息部分缺失时基因-环境交互作用的估计.方法 在Stata 9.0软件上采用Monte Carlo方法模拟不同基因信息缺失比例数据,对缺失数据采用hot deck多重填补程序后分析和删除缺失值分析结果进行比较.结果 缺失数据<50%时,hotdeck多重填补后分析和删除缺失值分析对环境主效应、基因主效应以及基因-环境交互作用的估计系数接近完全数据的系数,随缺失比例的增加,两种方法的估计方差均增加,但hot deck多重填补估计方差小于删除缺失值分析.结论 不完全病例对照研究中,对照组基因信息缺失比例<50%时,可以用hot deck填补方法充分利用已有的信息估计基因-环境的交互作用,提高估计精度.
英文摘要:
      Objective To discuss the estimation on gene-environment interaction in partial case- control studies when gene information of the controls was partly missing.Methods The results of hot deck multiple imputation and listwise deletion analysis were compared when missing data was generated using Monte Carlo method in Stata 9.0.Results Coefficients of environment effect,gene effect and gene- environment interaction were respectively estimated by means of hot deck multiple imputation and listwise deletion when approaching to those complete data with missing part less than 50 percent.Both estimated variances of the two methods were increasing with the increased proportion of missing data,but the estimated variance of hot deck multiple imputation was smaller than the one with listwise deletion in each proportion.Conclusion Hot deck imputation could be adopted to make full use of existing information to estimate gene-environment interaction in the partial case-control study when missing proportion of gene data of controls was less than 50 percent so as to increase the precision of the estimation.
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