Logistic回归中出现P值与OR的95%置信区间(CI)结果矛盾

2013-08-16 MedSci MedSci原创

    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

    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。之所以发生这种情况,还与变量有关。有些人采取如下方法:一般都是合并变量的例数,回避这一问题。实际上,可能有如下一些原因:1:存在多重共线性,多重共线性会产生大的标准误,导致单因素分析中Wald检验中P值过大,虽然标准误增大,会使OR的95%置信区间变宽,95%CI的上线或下线特别接近1但还未超过1这个界限,所以出现了P>0.05,但OR的95%置信区间却不包括1。    解决的办法是可以利用逐步筛选变量的方法找出与因变量相关的变量,其他没有进入模型的变量在单因素分析中不给予分析。此外,还可以设法将彼此高度相关的自变量先综合成新变量,然后做因变量关于综合变量

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    2016-01-21 yoga2008

    very good very good ,我要好好学习!

    0

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    2016-01-08 qingfengqishi5

    收藏了

    0

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  5. [GetPortalCommentsPageByObjectIdResponse(id=58674, encodeId=107d586e410, content=very good very good ,我要好好学习!, beContent=null, objectType=article, channel=null, level=null, likeNumber=55, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://wx.qlogo.cn/mmopen/NUyjXTCJjo6lR0HdZibhWZ3RhdaUDK6KyHGK2SicUtCduBWvF8hm7GFsXwViaPMPK97jxoI2XTaHOkOtJADxRrqzfrFIK5UtjJ5/0, createdBy=73f21396495, createdName=yoga2008, createdTime=Thu Jan 21 15:18:00 CST 2016, time=2016-01-21, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=54732, encodeId=efd554e3239, content=收藏了, beContent=null, objectType=article, channel=null, level=null, likeNumber=102, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://wx.qlogo.cn/mmopen/jW482SpianMayicTRbRZ5RzTetibytbqFDmFITWHyBWbxU7S9MYibgPSqvu0sYteH0N6zXqbU0Kf3Mbdb7yWM1Kud3zPgYBibE2SZ/0, createdBy=da7696924, createdName=qingfengqishi5, createdTime=Fri Jan 08 20:55:00 CST 2016, time=2016-01-08, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=2055370, encodeId=279320553e0b7, content=<a href='/topic/show?id=c606e965446' target=_blank style='color:#2F92EE;'>#置信区间#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=30, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=79654, encryptionId=c606e965446, topicName=置信区间)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=e03212, createdName=liao1619, createdTime=Fri Nov 01 18:51:00 CST 2013, time=2013-11-01, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1746722, encodeId=56dd1e4672255, 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=18, 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=Wed Oct 30 23:51:00 CST 2013, time=2013-10-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=6197, encodeId=97c7619e60, content=非常有有用,值得看看,我也碰到过这种问题。, beContent=null, objectType=article, channel=null, level=null, likeNumber=145, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=a3f688392, createdName=zjg197415, createdTime=Mon Oct 14 10:49:00 CST 2013, time=2013-10-14, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1905751, encodeId=29b21905e5151, content=<a href='/topic/show?id=9dc4109964f' target=_blank style='color:#2F92EE;'>#Logistic#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=23, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=10996, encryptionId=9dc4109964f, topicName=Logistic)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=afa4194, createdName=cenghis, createdTime=Sun Jul 27 11:51:00 CST 2014, time=2014-07-27, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1455099, encodeId=e388145509956, content=<a href='/topic/show?id=bebe8032fc' target=_blank style='color:#2F92EE;'>#GIST#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=22, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=8032, encryptionId=bebe8032fc, topicName=GIST)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=6e445632366, createdName=july_977, createdTime=Sun Aug 18 08:51:00 CST 2013, time=2013-08-18, status=1, ipAttribution=)]
    2013-10-14 zjg197415

    非常有有用,值得看看,我也碰到过这种问题。

    0

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    2014-07-27 cenghis
  7. [GetPortalCommentsPageByObjectIdResponse(id=58674, encodeId=107d586e410, content=very good very good ,我要好好学习!, beContent=null, objectType=article, channel=null, level=null, likeNumber=55, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://wx.qlogo.cn/mmopen/NUyjXTCJjo6lR0HdZibhWZ3RhdaUDK6KyHGK2SicUtCduBWvF8hm7GFsXwViaPMPK97jxoI2XTaHOkOtJADxRrqzfrFIK5UtjJ5/0, createdBy=73f21396495, createdName=yoga2008, createdTime=Thu Jan 21 15:18:00 CST 2016, time=2016-01-21, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=54732, encodeId=efd554e3239, content=收藏了, beContent=null, objectType=article, channel=null, level=null, likeNumber=102, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://wx.qlogo.cn/mmopen/jW482SpianMayicTRbRZ5RzTetibytbqFDmFITWHyBWbxU7S9MYibgPSqvu0sYteH0N6zXqbU0Kf3Mbdb7yWM1Kud3zPgYBibE2SZ/0, createdBy=da7696924, createdName=qingfengqishi5, createdTime=Fri Jan 08 20:55:00 CST 2016, time=2016-01-08, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=2055370, encodeId=279320553e0b7, content=<a href='/topic/show?id=c606e965446' target=_blank style='color:#2F92EE;'>#置信区间#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=30, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=79654, encryptionId=c606e965446, topicName=置信区间)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=e03212, createdName=liao1619, createdTime=Fri Nov 01 18:51:00 CST 2013, time=2013-11-01, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1746722, encodeId=56dd1e4672255, 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=18, 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=Wed Oct 30 23:51:00 CST 2013, time=2013-10-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=6197, encodeId=97c7619e60, content=非常有有用,值得看看,我也碰到过这种问题。, beContent=null, objectType=article, channel=null, level=null, likeNumber=145, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=a3f688392, createdName=zjg197415, createdTime=Mon Oct 14 10:49:00 CST 2013, time=2013-10-14, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1905751, encodeId=29b21905e5151, content=<a href='/topic/show?id=9dc4109964f' target=_blank style='color:#2F92EE;'>#Logistic#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=23, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=10996, encryptionId=9dc4109964f, topicName=Logistic)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=afa4194, createdName=cenghis, createdTime=Sun Jul 27 11:51:00 CST 2014, time=2014-07-27, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1455099, encodeId=e388145509956, content=<a href='/topic/show?id=bebe8032fc' target=_blank style='color:#2F92EE;'>#GIST#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=22, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=8032, encryptionId=bebe8032fc, topicName=GIST)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=6e445632366, createdName=july_977, createdTime=Sun Aug 18 08:51:00 CST 2013, time=2013-08-18, status=1, ipAttribution=)]
    2013-08-18 july_977

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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,

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