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Survminer,生存软件包:“ survdiff”对数秩检验与“常规”对数秩检验有什么区别?

[英]Survminer, survival package: What is the difference between the “survdiff” log-rank and “regular” log-rank tests?

I am using the survminer survival package in R. To compute p values to compare survival curves, I am using the surf_pvalue function. 我在R中使用survminer生存软件包。为了计算p值以比较生存曲线,我使用了surf_pvalue函数。

With this function, you can determine the log-rank p value in two different ways. 使用此功能,您可以通过两种不同的方法确定对数秩p值。 One is called "survdiff", the other "1" or "LR". 一个称为“ survdiff”,另一个称为“ 1”或“ LR”。 See this link for more info. 有关更多信息,请参见此链接 The second says that it is a "regular log-rank test, sensitive to detect late differences" , but what are the differences between the two. 第二个说这是“常规对数秩检验,对检测后期差异很敏感” ,但是两者之间有什么区别。 Does anyone know? 有人知道吗?

Thank you. 谢谢。

The methods "survdiff" , "log-rank" , "LR" , "1" all give the same results. 方法"survdiff""log-rank""LR""1"都给出相同的结果。

Here is a minimal & reproducible example 这是一个最小且可重现的示例

library(survival)
library(survminer)

fit <- surv_fit(Surv(time, status) ~ sex, data = colon)

methods <- c("survdiff", "log-rank", "LR", "1")
purrr::imap(setNames(methods, methods), ~surv_pvalue(fit, method = .x))
#$survdiff
#  variable      pval   method pval.txt
#1      sex 0.6107936 Log-rank p = 0.61
#
#$`log-rank`
#  variable      pval   method pval.txt
#1      sex 0.6107936 Log-rank p = 0.61
#
#$LR
#  variable      pval   method pval.txt
#1      sex 0.6107936 Log-rank p = 0.61
#
#$`1`
#  variable      pval   method pval.txt
#1      sex 0.6107936 Log-rank p = 0.61

If we take a look at the source code of survminer we see that 如果我们看一下survminer源代码 ,我们会看到

[...]
allowed.methods <- c("survdiff", "log-rank", "LR", "1",
                       "n", "Gehan-Breslow", "GB",
                       "sqrtN", "Tarone-Ware", "TW",
                       "S1", "Peto-Peto", "PP",
                       "S2", "modified Peto-Peto", "mPP",
                       "FH_p=1_q=1", "Fleming-Harrington(p=1, q=1)", "FH")

method.names <- c(rep("survdiff", 4),
                rep(c("n", "sqrtN", "S1", "S2", "FH_p=1_q=1"), each = 3))
[...]

All four methods are unified as method.names = "survdiff" . 所有这四个方法都统一为method.names = "survdiff"

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