Summarise numeric variable using arithmetic mean (possibly segmented)

Takes one numeric variable and returns a tidy dataframe, including relative mean and absolute size of each group. The variable can be further segmented by another categorical variable. Can also take survey weights. Returns 95% confidence intervals.

Usage

stem_summarise_num(
  data,
  item,
  group = NULL,
  weight = NULL,
  long = FALSE,
  collapse_group = NULL,
  na.rm = TRUE,
  return_n = FALSE
)

Arguments

data: Dataframe including data to be analyzed
item: Variable to be summarised
group: Optional segmenting variable
weight: Optional survey weights
long: Returns data in long format. Useful if multiple dataframes are to be merged
collapse_group: Named list. Optionally collapses (or renames) categories of the group variable
na.rm: If TRUE (default), NA values in the item are dropped from the calculations and observations with an NA group are excluded. If FALSE, NA item values are kept (so the mean is NA) and NA group values form their own group.
return_n: If TRUE, returns absolute group sizes.

Value

Tidy dataframe

Examples

trust |> stem_summarise_num(age,
                            group = eu_index,
                            weight = W,
         collapse_group = list(`Neutral or no opinion` = c("Neutral", "Doesn't Know")))
#> # A tibble: 3 × 4
#>   eu_index               mean mean_low mean_upp
#>   <fct>                 <dbl>    <dbl>    <dbl>
#> 1 Likes EU               39.2     38.7     39.6
#> 2 Neutral or no opinion  39.0     38.5     39.4
#> 3 Dislikes EU            38.2     37.5     38.9