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趋势检验中P for trend和Per 1 SD，这些是啥东西？

2018-11-06 MedSci MedSci原创

趋势检验
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案例。临床上检验一个自变量与因变量的关系，尤其是自变量分为很多等级的话，往往要做p for trend检验，即常见的趋势分析。但是，有时却会见到Per 1 SD，这又是什么呢？ 先看案例 The level of galactose-deficient IgA1 in the sera of patients with IgA nephropathy is associated with di

案例。临床上检验一个自变量与因变量的关系，尤其是自变量分为很多等级的话，往往要做p for trend检验，即常见的趋势分析。但是，有时却会见到Per 1 SD，这又是什么呢？ 先看案例 The level of galactose-deficient IgA1 in the sera of patients with IgA nephropathy is associated with disease progression. 该文研究Gd-IgA1与IgA肾病的疾病进展的关系。作者本人并没有将原始测量的Gd-IgA1（U/ml）带入COX回归模型。而采用了两种变换的方式： 图1 1、quarties quarties进行统计分析。就是将原始数据进行四分位数间距分组，然后从小到大定义为1、2、3、4个等级。然而本文作者并没有做P for trend，而是把1、2、3、4当做无序分类，然后设置哑变量，以1为参照，得出具体的回归系数。 2、Per 1 sd Per 1 sd是指，原始数据每升高1个标准差，效应量发生的风险，本例为HR。可是这是怎么实现的呢？1个标准差是多少呢? 怎么实现这

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    2019-04-05 14598488m86暂无昵称

    牛

    0

  2. [GetPortalCommentsPageByObjectIdResponse(id=364170, encodeId=f1433641e0f1, content=牛, beContent=null, objectType=article, channel=null, level=null, likeNumber=61, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=34155072871, createdName=14598488m86暂无昵称, createdTime=Fri Apr 05 19:22:56 CST 2019, time=2019-04-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1905713, encodeId=d4311905e13f8, content=<a href='/topic/show?id=2ebd1e7981a' target=_blank style='color:#2F92EE;'>#trend#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=41, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=17798, encryptionId=2ebd1e7981a, topicName=trend)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=ced3193, createdName=freve, createdTime=Tue Sep 10 19:37:00 CST 2019, time=2019-09-10, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1727707, encodeId=58541e277077f, content=<a href='/topic/show?id=986913980dd' target=_blank style='color:#2F92EE;'>#PE#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=36, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=13980, encryptionId=986913980dd, topicName=PE)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=f06c33759375, createdName=feather89, createdTime=Wed Oct 09 05:37:00 CST 2019, time=2019-10-09, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1488545, encodeId=c90214885450a, content=<a href='/topic/show?id=5bc8929620b' target=_blank style='color:#2F92EE;'>#趋势检验#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=36, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=92962, encryptionId=5bc8929620b, topicName=趋势检验)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=4cf58431529, createdName=changfy, createdTime=Thu Nov 08 12:37:00 CST 2018, time=2018-11-08, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=351757, encodeId=4217351e5704, content=好, beContent=null, objectType=article, channel=null, level=null, likeNumber=59, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=0aa31415219, createdName=orangesking, createdTime=Tue Nov 06 22:23:25 CST 2018, time=2018-11-06, status=1, ipAttribution=)]
    2019-09-10 freve

    #trend#

    0

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    2019-10-09 feather89

    #PE#

    0

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    2018-11-08 changfy

    #趋势检验#

    0

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    2018-11-06 orangesking

    好

    0

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趋势检验在临床研究中用得并不太多，但却非常重要。如果能证明各等级间存在线性趋势（如剂量-反应关系或剂量-效应关系），那么该研究的证据等级非常高。最新的GRADE分级将剂量-反应关系放在较高等级。想想也是，两组间存在差异可能是偶然抽样得到的结果，也可能是系统误差导致的。但如果实际上没有等级趋势，抽样样本发现某种趋势的可能性要小很多。随着统计软件功能的强大，很多人习惯通过各种模型回答趋势性问题，比如，