有数据类型如下
Tumor Site freq
1 HMF HNK 22
2 HMF TNK 2
3 HMF EXT 10
4 SSM HNK 16
5 SSM TNK 54
6 SSM EXT 115
7 NOD HNK 19
8 NOD TNK 33
9 NOD EXT 73
10 IND HNK 11
11 IND TNK 17
12 IND EXT 28
用R作泊松回归tumor.fit2 <- glm(freq~Tumor*Site,family=poisson,data=tumordata)
回归结果如下
Call:
glm(formula = freq ~ Tumor * Site, family = poisson, data = tumordata)
Deviance Residuals:
[1] 0 0 0 0 0 0 0 0 0 0 0 0
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.0910 0.2132 14.498 < 2e-16 ***
TumorIND -0.6931 0.3693 -1.877 0.060511 .
TumorNOD -0.1466 0.3132 -0.468 0.639712
TumorSSM -0.3185 0.3286 -0.969 0.332432
SiteEXT -0.7885 0.3814 -2.067 0.038701 *
SiteTNK -2.3979 0.7385 -3.247 0.001167 **
TumorIND:SiteEXT 1.7228 0.5216 3.303 0.000957 ***
TumorNOD:SiteEXT 2.1345 0.4602 4.638 3.52e-06 ***
TumorSSM:SiteEXT 2.7608 0.4655 5.931 3.00e-09 ***
TumorIND:SiteTNK 2.8332 0.8338 3.398 0.000679 ***
TumorNOD:SiteTNK 2.9500 0.7927 3.721 0.000198 ***
TumorSSM:SiteTNK 3.6143 0.7915 4.566 4.96e-06 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 2.9520e+02 on 11 degrees of freedom
Residual deviance: 8.2157e-15 on 0 degrees of freedom
AIC: 83.111
Number of Fisher Scoring iterations: 3
请问下面的系数代表什么意义,在模型中的数据应该是什么样子的。
TumorIND:SiteEXT 1.7228 0.5216 3.303 0.000957 ***
TumorNOD:SiteEXT 2.1345 0.4602 4.638 3.52e-06 ***
TumorSSM:SiteEXT 2.7608 0.4655 5.931 3.00e-09 ***
TumorIND:SiteTNK 2.8332 0.8338 3.398 0.000679 ***
TumorNOD:SiteTNK 2.9500 0.7927 3.721 0.000198 ***
TumorSSM:SiteTNK 3.6143 0.7915 4.566 4.96e-06 ***