作为未正确评估的列表提供的参数

Question

我正在开发一个自定义函数，其目标是为分组变量的所有组合运行一个函数（..f），grouping.var为给定的数据帧提供，然后使用broom包将这些结果整理到数据帧中。

这是我写的自定义函数。请注意，...提供给..f，而broom::tidy方法的其他参数则通过tidy.args列表提供。

# setup
set.seed(123)
library(tidyverse)
options(pillar.sigfig = 8)

# custom function
grouped_tidy <- function(data,
                         grouping.vars,
                         ..f,
                         ...,
                         tidy.args = list()) {
  # check how many variables were entered for grouping variable vector
  grouping.vars <-
    as.list(rlang::quo_squash(rlang::enquo(grouping.vars)))
  grouping.vars <-
    if (length(grouping.vars) == 1) {
      grouping.vars
    } else {
      grouping.vars[-1]
    }

  # quote all argument to `..f`
  dots <- rlang::enquos(...)

  # running the grouped analysis
  df_results <- data %>%
    dplyr::group_by(.data = ., !!!grouping.vars, .drop = TRUE) %>%
    dplyr::group_map(
      .tbl = ., 
      .f = ~ broom::tidy(
        x = rlang::exec(.fn = ..f, !!!dots, data = .x),
        unlist(tidy.args)
    ))

  # return the final dataframe with results
  return(df_results)
}

如下面的例子所示，尽管这个函数有效，但我怀疑tidy.args列表是否得到了适当的评估，因为无论我选择什么conf.level，我总是得到相同的结果到小数点后4位。

• 95% CI

# using the function to get 95% CI
grouped_tidy(
  data = ggplot2::diamonds,
  grouping.vars = c(cut),
  ..f = stats::lm,
  formula = price ~ carat - 1,
  tidy.args = list(conf.int = TRUE, conf.level = 0.95)
)

#> # A tibble: 5 x 8
#> # Groups:   cut [5]
#>   cut       term   estimate std.error statistic p.value  conf.low conf.high
#>   <ord>     <chr>     <dbl>     <dbl>     <dbl>   <dbl>     <dbl>     <dbl>
#> 1 Fair      carat 4510.7919 42.614474 105.85117       0 4427.2062 4594.3776
#> 2 Good      carat 5260.8494 27.036670 194.58200       0 5207.8454 5313.8534
#> 3 Very Good carat 5672.5054 18.675939 303.73334       0 5635.8976 5709.1132
#> 4 Premium   carat 5807.1392 16.836474 344.91422       0 5774.1374 5840.1410
#> 5 Ideal     carat 5819.4837 15.178657 383.39911       0 5789.7324 5849.2350

• 99% CI

# using the function to get 99% CI
grouped_tidy(
  data = ggplot2::diamonds,
  grouping.vars = c(cut),
  ..f = stats::lm,
  formula = price ~ carat - 1,
  tidy.args = list(conf.int = TRUE, conf.level = 0.99)
)

#> # A tibble: 5 x 8
#> # Groups:   cut [5]
#>   cut       term   estimate std.error statistic p.value  conf.low conf.high
#>   <ord>     <chr>     <dbl>     <dbl>     <dbl>   <dbl>     <dbl>     <dbl>
#> 1 Fair      carat 4510.7919 42.614474 105.85117       0 4427.2062 4594.3776
#> 2 Good      carat 5260.8494 27.036670 194.58200       0 5207.8454 5313.8534
#> 3 Very Good carat 5672.5054 18.675939 303.73334       0 5635.8976 5709.1132
#> 4 Premium   carat 5807.1392 16.836474 344.91422       0 5774.1374 5840.1410
#> 5 Ideal     carat 5819.4837 15.178657 383.39911       0 5789.7324 5849.2350

关于如何更改函数以便broom::tidy正确评估参数列表的任何想法？