危险度分析和 logistic 回归
DESCRIPTION
危险度分析和 Logistic 回归. 第十七章. 上海第二医科大学 生物统计教研室. 危险度分析和 LOGISTIC 回归主要用于研究影响肿瘤和其它各种疾病的发病因素或预后因素。 一般的相对危险度计算通常用于单因素分析。 LOGISTIC 回归可用于多因素分析。. 第十七章危险度分析和 Logistic 回归. 第一节 发病危险度比较的统计指标. 病因分析(或预后分析)的目的:找出影响疾病发生(或预后好坏)的原因及其影响的强度。 如果某因素对疾病发生有影响,就称该因素与疾病发病有联系,而联系的强度则反映该因素对疾病发生影响的大小。 - PowerPoint PPT PresentationTRANSCRIPT
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Logistic
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LOGISTIC
LOGISTIC Logistic
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,,
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RISK , ,
- (relative risk)RR,P1P0,: RR>1,,;RR
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17.1 ,, ,,:
(%)
12 351 363 P1=3.3 1 817 818 P0=0.12 13 1168 1181
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RR= =27.627.6
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(cohort study), ,,,,, ,
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: a b c d
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=a/(a+b)
=c/(c+d)
=[a/(a+b)]/[c/(c+d)]
:
a
b
a+b
c
d
c+d
a+c
b+d
n=a+b+c+d
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RR H0:1, RR=1 H1:1,RR1 2MH=[(ad-bc)2(n-1)]/[(a+b)(c+d)(a+c)(b+d)] 22n/(n-1) 2MH =[(n-1)/n]2 2=(ad-bc)2n/[(a+b)(c+d)(a+c)(b+d)] n,,,2Yates2
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95%,99%
AR95%
_758896506.unknown
_758896569.unknown
_758896664.unknown
_758896465.unknown
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21.2 ,609,,17.1 27(a) 95(b) 122 44(c) 443(d) 487 71 538 609
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,,2.45
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=(27/122)/(44/487)=2.45
H0: RR=1
H1:RR1
=[(27443-4495)2(609-1)]/(12248771538)=16.22
=16.22>20.01 , P
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(Case-Control Study),,,,, ,,,,
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a
b
c
d
a
b
c
d
,t
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(Grouped Case-Control Study)(odds),(odds ratio)
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(odds), Odds=P/1-P=[a/(a+b)]/[b/(a+b)]=a/b=[c/(c+d)]/[d/(c+d)]=c/d
OR(odds ratio) OR=[a/b]/[c/d]=ad/bc (P320)
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21.3 ,,183()183(),:17.2 () 55 128 183 () 19 164 183 74 292 366
- (17.19), =(55164)/(19128)=3.71H0:=1H1:1 =[(55164-19128)2(366-1)]/(74292183183)=21.89 >20.01=6.635,P
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, ,,, ,,,,2(,)
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17.3 300 56 294 21 6 35 700 944 606 79 94 865
=(300944)/(56700)=7.22
=(29479)/(60621)=1.83
=(6865)/(9435)=1.58
=7.22, ,
_758908104.unknown
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,,1.83,1.58 (Stratified Analysis)(,,),,
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K22:P32317.4512 3 41
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,,,,, ,,(Paired Case-Contral Study)
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, , ,,,,,,
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Logistic ,y Logisticy,,, 10SASlogistic12Y=1 Y=2 Logistic
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Yresponse variable)X: (covariate),(explanatory) , X, logisticPY1,P=P(Y=1)Q=1-P,Q=P(Y=2) PXi Logistic
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P=[exp(b0+b1x1++bmxm)]/[1+exp(b0+b1x1++bmxm)] Q=1-P=1/[1+exp(b0+b1x1++bmxm)] P/(1-P)=exp(b0+b1x1++bmxm)y=ln[P/(1-P)]logit,, y=ln[p/(1-p)]= b0+b1x1++bmxm Logistic
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SASLogisticLogistic Logistic
Logistic
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1. P2.
Logistic
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3. Xibi Xiexp(bi)(1) Xi1=0= exp(bi)Logistic
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2Xi0=1=2=3= exp(bi) exp(3bi)3Xi exp(bi)6035exp(25bi)Logistic
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4. bi 5. XLXKXLK= XL*XK bLKXLXK6. LogisticLogistic
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17 6 23 5 87 92 22 93 115
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Sensitivity= 17/23=73.9%specificity= 87/92=94.6%correct= / 17+87/ 115=90.4%false positive rate= 5/22=22.7%false negative rate= 6/93=6.5%
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LOGISTIC P/1PEXP-17.96+3.63X5+1.60X6+1.91X7+2.57X8 X
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12X1A, =1, =0YY3=1=0 3 SAS6.12 t LOGISTIC3YYP0.05
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1 RCPP 2LOGISTIC
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P
-2.8770 2.0954 0.1697 . X3C 2.2844 1.0210 0.0253 0.519452 X5 1.0102 0.3147 0.0013 0.931773 X6 1.6321 0.5449 0.0027 0.837360 X8 -0.5764 0.1874 0.0021 -0.917033 X9 0.000386 0.000186 0.0384 0.392918
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3 e2.2844=9.821 e1.0102=2.751 e1.6321=5.111g/L e0.5764=1.781000/mm3e0.386 =1.47
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33
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LOGISTICy=ln(P/(1-P))= -2.8770+2.2844 +1.0102 +1.6321 -0.5764 g/L +0.000386 /mm3
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LOGISTIC98P0.5P0.5 47 7 54 9 35 44 56 42 98
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Sensitivity= 47/54=87.0%specificity= 35/44=79.5%correct= / 47+35/ 98=83.7%false positive rate= 9/56=16.1%false negative rate= 7/42=16.7%