如何在用户定义的公式中调用命名变量？使用 dplyr::summarise()

如何解决如何在用户定义的公式中调用命名变量？使用 dplyr::summarise()

我正在尝试使用 ci.auc() 包中的 pROC 函数创建一个函数来提取“曲线下面积”估计的 2 个命名变量的置信区间，但它产生并出错： Error in model.frame.default(formula = anchor,data = namedvar1,: 'data' must be a data.frame,environment,or list 。 如何解决这个问题？有没有更好的方法来指定从哪个数据框绘制命名变量？

原始代码工作正常：

library(pROC)

df <- structure(list(anchor1 = c(1,1,0),namedvar1 = c(0.603,-0.006,0.263,-0.089),namedvar2 = c(0.150346263678009,0.388250731888,-0.2579633906095,0.2562039253,0.139948502022,-0.267652844)),row.names = c(6L,7L,12L,13L,19L,29L),class = "data.frame")


# Base example with to extract CI bounds & estimate
 as.numeric (ci.auc ( roc (df$anchor1,df$namedvar1,smooth = FALSE,direction = "<",ci = TRUE,boot.stratified = TRUE )  ) )

# Output looks good:
[1] 0.2908208 0.7777778 1.0000000

太好了，所以我将上述内容整合到我的函数中（我想为多个命名变量执行此操作）：

### CREATE FUNC TO CALCULATE AUC and 95% CIs

new_roc <- function( df,anchor,na.rm = T) {
  anchor <- enquo(anchor)

  # Calculate and save this information as an object
  dplyr::summarise(df,# ci.auc() & roc() are from pROC package
                   "Var1 AUC CIs"  = as.numeric (ci.auc (roc (anchor,namedvar1,boot.stratified = TRUE )  ) ),"Var2 AUC CIs"  = as.numeric (ci.auc (roc (anchor,namedvar2,boot.stratified = TRUE )  ) )
  ) 
}

但是当我测试它时，我得到一个错误！

# Try the function

new_roc(df,anchor1 )

# Error output: 
`Error in model.frame.default(formula = anchor,:'data' must be a data.frame,or list`

我试过 class(df)，结果确实是 data.frame，所以不确定是什么问题。

为了尝试隔离问题，我尝试了内部代码，但首先指定了数据框 - 不起作用：

 # Doesn't work to pipe the df
df %>% 
  as.numeric (ci.auc (roc (anchor1,boot.stratified = TRUE )  ) )
  
## Produces error

Error in roc(anchor1,: 
  object 'anchor1' not found
 

也许我不必要地使用了 dplyr？是否有不同的方法来指定从哪个数据框绘制命名变量？谢谢！

我也尝试过放弃 dplyr 并直接调用数据帧，但也不起作用：

new_roc <- function( df,na.rm = T) {
  anchor <- enquo(anchor)

  # Calculate and save this information as an object
                   # ci.auc() & roc() are from pROC package
                   "Var1 AUC CIs"  = as.numeric (ci.auc (roc (data[[anchor],data[[namedvar1],"Var2 AUC CIs"  = as.numeric (ci.auc (roc (data[[anchor],data[[namedvar2],boot.stratified = TRUE )  ) )
  ) 
}

# Produces a different Error:
Error in .subset2(x,i,exact = exact) : 
  invalid subscript type 'language' 

解决方法

我们需要使用 !! 与 enquo 进行评估，或者可以将其修改为 {{}}

new_roc <- function( df,anchor,na.rm = TRUE) {



      dplyr::summarise(df,`Var1 AUC CIs`  = as.numeric (ci.auc (roc ({{anchor}},namedvar1,smooth = FALSE,direction = "<",ci = TRUE,boot.stratified = TRUE )  ) ),`Var2 AUC CIs`  = as.numeric (ci.auc (roc ({{anchor}},namedvar2,boot.stratified = TRUE )  ) )
     ) 
  }

-测试

new_roc(df,anchor1)
#Setting levels: control = 0,case = 1
#Setting levels: control = 0,case = 1
#  Var1 AUC CIs Var2 AUC CIs
#1    0.2908208    0.0000000
#2    0.7777778    0.3333333
#3    1.0000000    0.9866547

与

相同

as.numeric (ci.auc ( roc (df$anchor1,df$namedvar1,boot.stratified = TRUE )  ) )
#Setting levels: control = 0,case = 1
#[1] 0.2908208 0.7777778 1.0000000

,

如果您不想使用 dplyr 方法，请尝试：

library(pROC)

new_roc <- function( df,anchor) {
  
data.frame(Var1_AUC_CIs = as.numeric(ci.auc(roc(df[[anchor]],boot.stratified = TRUE))),Var2_AUC_CIs = as.numeric(ci.auc(roc(df[[anchor]],df$namedvar2,boot.stratified = TRUE)))) 
}
new_roc(df,'anchor1')

#  Var1_AUC_CIs Var2_AUC_CIs
#1    0.2908208    0.0000000
#2    0.7777778    0.3333333
#3    1.0000000    0.9866547