创建一个将其参数传递给 Surv 函数(或任何其他函数)的函数

Creating a function passing its arguments to the Surv function (or any other)

请考虑以下几点:

要创建生存曲线,可以使用 survival 包的 survfit 函数。

我的目标是编写一个函数(除其他外)创建这样一条曲线,但该函数应该适用于不同的 data.frames,其列名也不同。此外,分组变量将取决于相应的数据集。

我设法将不同的 data.frame 名称传递给函数,但为 survfitSurv 函数提供列名称对我不起作用。

非常感谢任何帮助。

在我看来,这是一个不同于简单地将 data.frame 列名称传递给函数的问题,如下所述:Pass a data.frame column name to a function

# required libraries
library(survival)
library(flexsurv)

#### Examples that work without own function ===================================
# survfit wit lung data
survfit(Surv(time = time, event = status) ~ 1, data = lung)
#> Call: survfit(formula = Surv(time = time, event = status) ~ 1, data = lung)
#> 
#>       n  events  median 0.95LCL 0.95UCL 
#>     228     165     310     285     363
survfit(Surv(time = time, event = status) ~ sex, data = lung)
#> Call: survfit(formula = Surv(time = time, event = status) ~ sex, data = lung)
#> 
#>         n events median 0.95LCL 0.95UCL
#> sex=1 138    112    270     212     310
#> sex=2  90     53    426     348     550

# survfit with bc data
survfit(Surv(time = rectime, event = censrec) ~ 1, data = bc)
#> Call: survfit(formula = Surv(time = rectime, event = censrec) ~ 1, 
#>     data = bc)
#> 
#>       n  events  median 0.95LCL 0.95UCL 
#>     686     299    1807    1587    2030

# Create variable function that takes on data specific arguments
SurvFun <- function(fun.time, fun.event, grouping = 1, fun.dat){
  survfit(Surv(time = fun.time, event = fun.event) ~ grouping, data = fun.dat)
}

#### Own function that doesn't work ============================================
# This should work for data = lung
SurvFun(fun.time = time, fun.event = status, grouping = 1, fun.dat = lung)
#> Error in Surv(time = fun.time, event = fun.event): Time variable is not numeric

reprex 创建于 2018-07-05 包 (v0.2.0).

当列名未被引号括起来时,它们将作为符号传递。传递符号比传递简单变量要困难得多。这也适用于公式。你需要做一些元编程才能工作。这是重新编写函数以使其正常工作的一种方法

SurvFun <- function(fun.time, fun.event, grouping = 1, fun.dat) {
  params <- list(fun.time = substitute(fun.time),
    fun.event = substitute(fun.event),
    grouping = substitute(grouping), 
    fun.dat = substitute(fun.data))
  expr <- substitute(survfit(Surv(time = fun.time, event = fun.event) ~ grouping, 
    data = fun.dat), params)
  eval.parent(expr)
}