Question

我试图将症状侧特定病变（二元）的患病率与一组患者的无症状侧患病率进行比较。

我已经进行过McNemar测试，以比较患者中症状性和无症状患者的患病率。

但是，我还要求进行条件逻辑回归。我不确定我的语法在分层方面是否正确：

summary(clogit(ds$symp ~  ds$asymp, strata(ds$ID), data=ds, method = "exact"))

R是否比较患者的两侧（症状与无症状）？或者我是否必须手动复制患者ID（症状侧的一个ID和无症状侧的一个ID）？

谢谢，

一个例子：

ID symp asymp
1   0   0
2   1   0
3   0   0
4   0   0
5   1   0
6   1   1
7   0   0
8   0   0
9   0   1
10  0   0

例如：患者2在症状侧有病变，患者9在无症状侧有病变。患者6双方。

Exact McNemar测试显示：

test <- table(df$symp, df$asymp)
    compare <- exact2x2(test, paired = TRUE, alternative = "two.sided", tsmethod = "central")
print(compare)
Exact McNemar test (with central confidence intervals)

data:  test
b = 1, c = 2, p-value = 1
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
 0.00847498 9.60452988
sample estimates:
odds ratio 
       0.5

然而，条件逻辑回归模型：

> summary(clogit(df$symp ~  df$asymp, strata(df$ID), data=df, method = "exact"))
Call:
coxph(formula = Surv(rep(1, 10L), df$symp) ~ df$asymp, data = df, 
    method = "exact")

  n= 10, number of events= 3 

        coef exp(coef) se(coef)     z Pr(>|z|)
df$symp 0.973     2.646    1.524 0.638    0.523

       exp(coef) exp(-coef) lower .95 upper .95
df$asymp 2.646      0.378    0.1334     52.46

Rsquare= 0.039   (max possible= 0.616 )
Likelihood ratio test= 0.4  on 1 df,   p=0.528
Wald test            = 0.41  on 1 df,   p=0.5232
Score (logrank) test = 0.43  on 1 df,   p=0.5127

条件逻辑回归：在主题匹配

0 个答案: