Polish

library(mRclwhip)

The idea behind mRclwhip::polish() is to create a more ‘complete product’ than what is returned from broom::tidy(), for example.

The function can either return a flextable::flextable() object if the argument .flextable = TRUE.
Or, if the argument .flextable = FALSE, then a list with two objects is returned where the first object in the list is a dataframe of the polished results that can be further manipulated.

The second object in the list is a vector of row numbers that can then be passed into flextable::padding() (after passing the dataframe into mRclwhip::format_flextable() of course) to pad the rows with factor levels.

The example at the end will provide further clarification.

Example using coxph()

mockstudy <- arsenal::mockstudy
coxph_res <- survival::coxph(survival::Surv(fu.time, fu.stat) ~ race + sex + bmi, data = mockstudy)

Hmisc::label(mockstudy$sex) <- "Gender"

coxph_res %>%
  polish(
    .header1 = list(values = c("", "HR (95% CI)")),
    exponentiate = T
  )

Example using lm()

mtcars <- mtcars %>%
  dplyr::mutate_at(dplyr::vars(gear, am, carb), as.character)

mtcars <- Hmisc::upData(
  mtcars,
  labels = c(mpg = "MPG",
             hp = "HP",
             gear = "# of gears",
             am = "Automatic",
             wt = "Weight",
             carb = "Carb"
             ),
  print = F
  )

lm_res <- lm(mpg ~ hp + gear + am + wt + carb, data = mtcars)

lm_res %>%
  polish(
    .header1 = list(values = c("", "Estimate (95% CI)"))
  )

Example using lm() with labels argument used correctly

mtcars <- mtcars %>%
  dplyr::mutate_at(dplyr::vars(gear, am, carb), as.character)

labs <- c(hp = "HP",
          gear = "# of gears",
          am = "Automatic",
          wt = "Weight",
          carb = "Carb"
          )

lm_res <- lm(mpg ~ hp + gear + am + wt + carb, data = mtcars)

lm_res %>%
  polish(
    .header1 = list(values = c("", "Estimate (95% CI)")),
    .labels = labs
  )

Example using lm() with labels argument used incorrectly

mtcars <- mtcars %>%
  dplyr::mutate_at(dplyr::vars(gear, am, carb), as.character)

labs <- c(mpg = "MPG",
          hp = "HP",
          gear = "# of gears",
          am = "Automatic",
          wt = "Weight",
          carb = "Carb"
)

lm_res <- lm(mpg ~ hp + gear + am + wt + carb, data = mtcars)

lm_res %>%
  polish(
    .header1 = list(values = c("", "Estimate (95% CI)")),
    .labels = labs
  )
#> Error: You provided 6 labels but your model has 5 covariate(s). Please provide the same number of labels as covariates.

Example using .flextable = FALSE where a list with a dataframe and a vector of row numbers is returned

mtcars <- mtcars %>%
  dplyr::mutate_at(dplyr::vars(gear, am, carb), as.character)

mtcars <- Hmisc::upData(
  mtcars,
  labels = c(mpg = "MPG",
             hp = "HP",
             gear = "# of gears",
             am = "Automatic",
             wt = "Weight",
             carb = "Carb"
             ),
  print = F
  )

lm_res <- lm(mpg ~ hp + gear + am + wt + carb, data = mtcars)

res <- lm_res %>%
  polish(
    .flextable = FALSE
  )

res
#> [[1]]
#> # A tibble: 12 x 2
#>    label_lev     Estimate            
#>    <chr>         <glue>              
#>  1 HP            -0.03 (-0.07, 0.02) 
#>  2 # of gears    <NA>                
#>  3 4             2.36 (-2.65, 7.37)  
#>  4 5             2.86 (-3.10, 8.83)  
#>  5 Automatic (1) 1.48 (-2.65, 5.60)  
#>  6 Weight        -2.03 (-4.38, 0.32) 
#>  7 Carb          <NA>                
#>  8 2             -1.29 (-4.57, 1.99) 
#>  9 3             -1.62 (-6.42, 3.17) 
#> 10 4             -3.55 (-8.78, 1.68) 
#> 11 6             -4.91 (-12.77, 2.96)
#> 12 8             -3.82 (-15.91, 8.26)
#> 
#> [[2]]
#> [1]  3  4  8  9 10 11 12

Returning the dataframe allows further manipulation if desired. The row numbers returned for the rows with factor levels can then be used in flextable::padding() to add padding

res[[1]] %>% 
  mRclwhip::format_flextable(header1 = list(values = c("", "Estimate (95% CI)"))) %>% 
  flextable::padding(i = res[[2]], j = 1, padding.left = 25)