1

我已经构建了一个 cox 回归：

Call:
coxph(formula = Surv(`infection time`, infection) ~ Treatment + 
    Gender + Race + Surface + head + buttock + trunk + up.leg + 
    low.leg + resp.tract, data = BurnData)

整体检验（可能性、Wald 和分数）的 p 值仅对似然比检验显着。这些检验评估$H_0$：所有$\beta$ = 0。检验统计量不一致，因此不能明确拒绝原假设。总体而言，该模型没有很好的拟合度。

我想了解协变量治疗，特别是我想知道两个治疗组感染前的时间是否有显着差异？从上面的输出我可以说协变量很重要，但这不一样吗？

我试过strata命令：

coxph(formula = Surv(`infection time`, infection) ~ strata(Treatment) + 
    Gender + Race + Surface + head + buttock + trunk + up.leg + 
    low.leg + resp.tract, data = BurnData)

  n= 154, number of events= 48 

                coef exp(coef)  se(coef)      z Pr(>|z|)  
Gender     -0.649207  0.522460  0.396943 -1.636   0.1019  
Race        1.997690  7.372010  1.016640  1.965   0.0494 *
Surface     0.003237  1.003243  0.009704  0.334   0.7387  
head       -0.082786  0.920548  0.344487 -0.240   0.8101  
buttock     0.560418  1.751404  0.421308  1.330   0.1835  
trunk       0.239397  1.270483  0.494814  0.484   0.6285  
up.leg     -0.432832  0.648669  0.375035 -1.154   0.2485  
low.leg    -0.164111  0.848648  0.373298 -0.440   0.6602  
resp.tract  0.077946  1.081065  0.351205  0.222   0.8244  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

           exp(coef) exp(-coef) lower .95 upper .95
Gender        0.5225     1.9140    0.2400     1.137
Race          7.3720     0.1356    1.0051    54.069
Surface       1.0032     0.9968    0.9843     1.023
head          0.9205     1.0863    0.4686     1.808
buttock       1.7514     0.5710    0.7670     3.999
trunk         1.2705     0.7871    0.4817     3.351
up.leg        0.6487     1.5416    0.3110     1.353
low.leg       0.8486     1.1783    0.4083     1.764
resp.tract    1.0811     0.9250    0.5431     2.152

Concordance= 0.67  (se = 0.066 )
Rsquare= 0.098   (max possible= 0.909 )
Likelihood ratio test= 15.89  on 9 df,   p=0.06912
Wald test            = 10.44  on 9 df,   p=0.3157
Score (logrank) test = 12.71  on 9 df,   p=0.1761

但是，现在治疗变量根本不存在。如果两个不同的组对感染时间有显着不同的影响，我该如何比较？

我也试过 anova comparison。以下是有效的方法吗？

fit_trt0 <- coxph(Surv(`infection time`,infection) ~ (Treatment==0) + Gender + Race + Surface + 
                   head + buttock + trunk + up.leg + low.leg + resp.tract, data=BurnData)
summary(fit_trt0)

fit_trt1 <- coxph(Surv(`infection time`,infection) ~ (Treatment==1) + Gender + Race + Surface + 
                   head + buttock + trunk + up.leg + low.leg + resp.tract, data=BurnData)
summary(fit_trt1)

anova(fit_trt0,fit_trt1)
4

0 回答 0