make_factor() takes a labelled vector and converts it to a factor variable
using the value labels. This works with numeric, character, and factor vectors.
Details
This function is very similar to haven::as_factor()
and
sjlabelled::as_label()
and is heavily based on both. However, it has some key differences. The main
difference compared to both functions is that make_factor() adds a
"transformation" attribute to the new variable indicating how it was
created. You can see this in the examples.
Compared to sjlabelled::as_label()
it is not as extensive. For example, while sjlabelled::as_label()
works with data.frames and vectors, make_factor() only works with vectors.
In addition, sjlabelled::as_label()
has many different arguments that enable you to control the appearance of the
labels, NAs, and other things. make_factor() on the other hand is much
simpler. Similarly,
haven::as_factor()
also enables more customization over the output of the labels. Another key
difference between this function and those is that if there are values without
labels, this function returns an error.
Examples
library(adlgraphs)
library(dplyr)
# let's make a new variable and data set
new_df <- test_data %>%
# convert top into a factor
mutate(top_f = make_factor(top))
# compare the "top_f" to "top"
new_df %>% select(top, top_f)
#> # A tibble: 250 × 2
#> top top_f
#> <dbl+lbl> <fct>
#> 1 1 [Strongly agree] Strongly agree
#> 2 2 [Somewhat agree] Somewhat agree
#> 3 2 [Somewhat agree] Somewhat agree
#> 4 3 [Somewhat disagree] Somewhat disagree
#> 5 2 [Somewhat agree] Somewhat agree
#> 6 4 [Strongly disagree] Strongly disagree
#> 7 2 [Somewhat agree] Somewhat agree
#> 8 2 [Somewhat agree] Somewhat agree
#> 9 2 [Somewhat agree] Somewhat agree
#> 10 4 [Strongly disagree] Strongly disagree
#> # ℹ 240 more rows
# check the attributes to see the label and transformation
attributes(new_df$top_f)
#> $levels
#> [1] "Strongly agree" "Somewhat agree" "Somewhat disagree"
#> [4] "Strongly disagree"
#>
#> $class
#> [1] "factor"
#>
#> $label
#> [1] "An ideal society requires some groups to be on top and others to be on the bottom"
#>
#> $transformation
#> Converted 'top' into a factor based on its value labels
#>