配对资料的条件Logistic回归分析

2014-05-06 MedSci MedSci原创

配对调查资料的条件 Logistic 回归分析 1. 1:1 病例对照研究的基本概念   在管理工作中,我们也经常要开展对照调查。例如为什么有的人患了胃癌,有的人却不会患胃癌?如果在同一居住地选取同性别、年龄相差仅 ±2 岁的健康人作对照调查,调查他们与患胃癌有关的各种影响因素,这就是医学上很常用的所谓“1:1 病例对照研究”。病例对照研究资料常用条件Logistic 回归分析

配对调查资料的条件 Logistic 回归分析 1. 1:1 病例对照研究的基本概念在管理工作中,我们也经常要开展对照调查。例如为什么有的人患了胃癌,有的人却不会患胃癌?如果在同一居住地选取同性别、年龄相差仅 ±2 岁的健康人作对照调查,调查他们与患胃癌有关的各种影响因素,这就是医学上很常用的所谓“1:1 病例对照研究”。 病例对照研究资料常用条件Logistic 回归分析。条件Logistic 回归模型(conditional logistic regression model,CLRM),下称CLRM 模型。 2. 条件Logistic 回归模型的一个实例某地在肿瘤防治健康教育、社区干预工作中做了一项调查,内容是三种生活因素与胃癌发病的关系。调查的三种生活因素取值见表 11-6。 请拟合条件Logistic 回归模型,说明胃癌发病的主要危险因素。 表 11-6  三种生活因素与胃癌发病关系的取值 ------------------------------------------------------------------------------------ 变 量

版权声明:
本网站所有内容来源注明为“梅斯医学”或“MedSci原创”的文字、图片和音视频资料,版权均属于梅斯医学所有。非经授权,任何媒体、网站或个人不得转载,授权转载时须注明来源为“梅斯医学”。其它来源的文章系转载文章,或“梅斯号”自媒体发布的文章,仅系出于传递更多信息之目的,本站仅负责审核内容合规,其内容不代表本站立场,本站不负责内容的准确性和版权。如果存在侵权、或不希望被转载的媒体或个人可与我们联系,我们将立即进行删除处理。
在此留言
评论区 (4)
#插入话题
  1. [GetPortalCommentsPageByObjectIdResponse(id=1671685, encodeId=d29b16e1685d9, content=<a href='/topic/show?id=c56c4051902' target=_blank style='color:#2F92EE;'>#回归分析#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=34, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=40519, encryptionId=c56c4051902, topicName=回归分析)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=a46f26833520, createdName=cenghis, createdTime=Sun Nov 30 00:34:00 CST 2014, time=2014-11-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1746726, encodeId=7e931e46726ec, content=<a href='/topic/show?id=88e91099e10' target=_blank style='color:#2F92EE;'>#logistic回归#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=10997, encryptionId=88e91099e10, topicName=logistic回归)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d3c135838005, createdName=xlwang2703, createdTime=Fri Jan 23 10:34:00 CST 2015, time=2015-01-23, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1905755, encodeId=5f261905e5554, content=<a href='/topic/show?id=9dc4109964f' target=_blank style='color:#2F92EE;'>#Logistic#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=10996, encryptionId=9dc4109964f, topicName=Logistic)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=afa4194, createdName=cenghis, createdTime=Fri Mar 27 10:34:00 CST 2015, time=2015-03-27, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1455104, encodeId=4c901455104be, content=<a href='/topic/show?id=bebe8032fc' target=_blank style='color:#2F92EE;'>#GIST#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=8032, encryptionId=bebe8032fc, topicName=GIST)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=a12645, createdName=智慧医人, createdTime=Thu May 08 07:34:00 CST 2014, time=2014-05-08, status=1, ipAttribution=)]
  2. [GetPortalCommentsPageByObjectIdResponse(id=1671685, encodeId=d29b16e1685d9, content=<a href='/topic/show?id=c56c4051902' target=_blank style='color:#2F92EE;'>#回归分析#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=34, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=40519, encryptionId=c56c4051902, topicName=回归分析)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=a46f26833520, createdName=cenghis, createdTime=Sun Nov 30 00:34:00 CST 2014, time=2014-11-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1746726, encodeId=7e931e46726ec, content=<a href='/topic/show?id=88e91099e10' target=_blank style='color:#2F92EE;'>#logistic回归#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=10997, encryptionId=88e91099e10, topicName=logistic回归)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d3c135838005, createdName=xlwang2703, createdTime=Fri Jan 23 10:34:00 CST 2015, time=2015-01-23, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1905755, encodeId=5f261905e5554, content=<a href='/topic/show?id=9dc4109964f' target=_blank style='color:#2F92EE;'>#Logistic#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=10996, encryptionId=9dc4109964f, topicName=Logistic)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=afa4194, createdName=cenghis, createdTime=Fri Mar 27 10:34:00 CST 2015, time=2015-03-27, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1455104, encodeId=4c901455104be, content=<a href='/topic/show?id=bebe8032fc' target=_blank style='color:#2F92EE;'>#GIST#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=8032, encryptionId=bebe8032fc, topicName=GIST)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=a12645, createdName=智慧医人, createdTime=Thu May 08 07:34:00 CST 2014, time=2014-05-08, status=1, ipAttribution=)]
  3. [GetPortalCommentsPageByObjectIdResponse(id=1671685, encodeId=d29b16e1685d9, content=<a href='/topic/show?id=c56c4051902' target=_blank style='color:#2F92EE;'>#回归分析#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=34, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=40519, encryptionId=c56c4051902, topicName=回归分析)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=a46f26833520, createdName=cenghis, createdTime=Sun Nov 30 00:34:00 CST 2014, time=2014-11-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1746726, encodeId=7e931e46726ec, content=<a href='/topic/show?id=88e91099e10' target=_blank style='color:#2F92EE;'>#logistic回归#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=10997, encryptionId=88e91099e10, topicName=logistic回归)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d3c135838005, createdName=xlwang2703, createdTime=Fri Jan 23 10:34:00 CST 2015, time=2015-01-23, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1905755, encodeId=5f261905e5554, content=<a href='/topic/show?id=9dc4109964f' target=_blank style='color:#2F92EE;'>#Logistic#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=10996, encryptionId=9dc4109964f, topicName=Logistic)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=afa4194, createdName=cenghis, createdTime=Fri Mar 27 10:34:00 CST 2015, time=2015-03-27, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1455104, encodeId=4c901455104be, content=<a href='/topic/show?id=bebe8032fc' target=_blank style='color:#2F92EE;'>#GIST#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=8032, encryptionId=bebe8032fc, topicName=GIST)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=a12645, createdName=智慧医人, createdTime=Thu May 08 07:34:00 CST 2014, time=2014-05-08, status=1, ipAttribution=)]
    2015-03-27 cenghis
  4. [GetPortalCommentsPageByObjectIdResponse(id=1671685, encodeId=d29b16e1685d9, content=<a href='/topic/show?id=c56c4051902' target=_blank style='color:#2F92EE;'>#回归分析#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=34, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=40519, encryptionId=c56c4051902, topicName=回归分析)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=a46f26833520, createdName=cenghis, createdTime=Sun Nov 30 00:34:00 CST 2014, time=2014-11-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1746726, encodeId=7e931e46726ec, content=<a href='/topic/show?id=88e91099e10' target=_blank style='color:#2F92EE;'>#logistic回归#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=10997, encryptionId=88e91099e10, topicName=logistic回归)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d3c135838005, createdName=xlwang2703, createdTime=Fri Jan 23 10:34:00 CST 2015, time=2015-01-23, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1905755, encodeId=5f261905e5554, content=<a href='/topic/show?id=9dc4109964f' target=_blank style='color:#2F92EE;'>#Logistic#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=10996, encryptionId=9dc4109964f, topicName=Logistic)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=afa4194, createdName=cenghis, createdTime=Fri Mar 27 10:34:00 CST 2015, time=2015-03-27, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1455104, encodeId=4c901455104be, content=<a href='/topic/show?id=bebe8032fc' target=_blank style='color:#2F92EE;'>#GIST#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=8032, encryptionId=bebe8032fc, topicName=GIST)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=a12645, createdName=智慧医人, createdTime=Thu May 08 07:34:00 CST 2014, time=2014-05-08, status=1, ipAttribution=)]
    2014-05-08 智慧医人

相关资讯

Logistic回归中出现P值与OR的95%置信区间(CI)结果矛盾

    在统计分析时,偶尔会遇到这样的情况:P值与OR的95%置信区间(CI)结果矛盾的情况,即P<0.05,但OR的95%置信区间却包括1;或者P>0.05,但OR的95%置信区间却不包括1。    在单因素Logistic回归和多因素Logistic回归中都出现了这样情况。一般认为,这种情况很难发生,因为它们检验具有一致性

二元Logistic回归案例分析

   二元Logistic,从字面上其实就可以理解大概是什么意思,Logistic中文意思为“逻辑”但是这里,并不是逻辑的意思,而是通过logit变换来命名的,二元一般指“两种可能性”就好比逻辑中的“是”或者“否”一样,Logistic 回归模型的假设检验——常用的检验方法有似然比检验(likelihood ratio test) 和 Wald检验)似然比检验的具体步骤如下:1

常用回归分析方法介绍:logistic回归、poission回归、probit回归、cox回归

回归分析可以说是统计学中内容最丰富、应用最广泛的分支。这一点几乎不带夸张。包括最简单的t检验、方差分析也都可以归到线性回归的类别。而卡方检验也完全可以用logistic回归代替。 众多回归的名称张口即来的就有一大片,线性回归、logistic回归、cox回归、poission回归、probit回归等等等等,可以一直说的你头晕。为了让大家对众多回归有一个清醒的认识,这里简单地做一下总结: 1,

利用倾向评分分层进行回归分析校正偏倚

在流行病学研究中, 分层分析和回归分析是资料分析阶段控制混杂偏倚的重要手段。将倾向评分法与传统的分层和回归结合,则可更有效地控制混杂偏倚,同时可以克服传统方法的一些局限性。一、原理和方法传统的分层分析是按照可能的混杂因素的不同水平将研究对象分为若干层,处在同一层的研究对象混杂因素趋于一致,可以直接比较效应。分别计算各层统计量(如t值x2 值)和效应尺度( 如OR 、均数差值) ,然后再用某种方法(

SPSS进行配对logistic回归(条件logistic回归)分析

一、概述 对病例和对照进行配比能控制影响实验效应的主要非处理因素,可以提高统计分析的效能,可分为1:1,1:n,m:n配对。SPSS中未提供专用的配对logistic回归的功能,通过变换,可以使用其他方法进行分析,常用的就是带有分层的Cox回归模型。 给每一条记录一个虚拟的生存时间,一般默认病例组的生存时间较对照组短,病例算事件发生,对照算作删失,把配对因素算作分层因素,消除配对因素的影响。

logistic回归由浅入深指南

多重线性回归的因变量y是连续型变量,自变量可以是连续的,也可以是分类的。但是现实中,因变量不一定都是连续的,还有其他分类的情形。比如想分析某病的危险因素,这时因变量就无法用连续资料来表示,而是表示为疾病的“有”或“无”两种情形。在这种情况下,用多重线性回归就不合适了, 而logistic回归则是处理这种数据的得力工具。 logistic回归主要在流行病学中应用较多,比较常用的情形是探索某疾病的危