The goal of freqtables is to quickly make tables of descriptive
statistics for categorical variables (i.e., counts, percentages,
confidence intervals). This package is designed to work in a tidyverse
pipeline, and consideration has been given to get results from R to
Microsoft Word ® with minimal pain.
You can install the released version of freqtables from
CRAN with:
install.packages("freqtables")And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("brad-cannell/freqtables")Because freqtables is intended to be used in a dplyr pipeline,
loading dplyr into your current R session is recommended.
library(dplyr)
library(freqtables)The examples below will use R’s built-in mtcars data set.
data("mtcars")The freq_table() function produces one-way and two-way frequency
tables for categorical variables. In addition to frequencies, the
freq_table() function displays percentages, and the standard errors
and confidence intervals of the percentages. For two-way tables only,
freq_table() also displays row (subgroup) percentages, standard
errors, and confidence intervals.
For one-way tables, the default 95 percent confidence intervals
displayed are logit transformed confidence intervals equivalent to those
used by Stata. Additionally, freq_table() will return Wald (“linear”)
confidence intervals if the argument to ci_type = “wald”.
For two-way tables, freq_table() returns logit transformed confidence
intervals equivalent to those used by Stata.
Here is an example of using freq_table() to create a one-way frequency
table with all function arguments left at their default values:
mtcars %>%
freq_table(am)
#> var cat n n_total percent se t_crit lcl ucl
#> 1 am 0 19 32 59.375 8.820997 2.039513 40.94225 75.49765
#> 2 am 1 13 32 40.625 8.820997 2.039513 24.50235 59.05775Here is an example of using freq_table() to create a two-way frequency
table with all function arguments left at their default values:
mtcars %>%
freq_table(am, cyl)
#> # A tibble: 6 × 17
#> row_var row_cat col_var col_cat n n_row n_total percent_total se_total
#> <chr> <chr> <chr> <chr> <int> <int> <int> <dbl> <dbl>
#> 1 am 0 cyl 4 3 19 32 9.38 5.24
#> 2 am 0 cyl 6 4 19 32 12.5 5.94
#> 3 am 0 cyl 8 12 19 32 37.5 8.70
#> 4 am 1 cyl 4 8 13 32 25 7.78
#> 5 am 1 cyl 6 3 13 32 9.38 5.24
#> 6 am 1 cyl 8 2 13 32 6.25 4.35
#> # … with 8 more variables: t_crit_total <dbl>, lcl_total <dbl>,
#> # ucl_total <dbl>, percent_row <dbl>, se_row <dbl>, t_crit_row <dbl>,
#> # lcl_row <dbl>, ucl_row <dbl>You can learn more about the freq_table() function and ways to adjust
default behaviors in vignette(“descriptive_analysis”).
The freq_test() function is an S3 generic. It currently has methods
for conducting hypothesis tests on one-way and two-way frequency tables.
Further, it is made to work in a dplyr pipeline with the freq_table()
function.
For the freq_table_two_way class, the methods used are Pearson’s
chi-square test of independence Fisher’s exact test. When cell counts
are <= 5, Fisher’s Exact Test is considered more reliable.
Here is an example of using freq_test() to test the equality of
proportions on a one-way frequency table with all function arguments
left at their default values:
mtcars %>%
freq_table(am) %>%
freq_test() %>%
select(var:percent, p_chi2_pearson)
#> var cat n n_total percent p_chi2_pearson
#> 1 am 0 19 32 59.375 0.2888444
#> 2 am 1 13 32 40.625 0.2888444Here is an example of using freq_test() to conduct a chi-square test
of independence on a two-way frequency table with all function arguments
left at their default values:
mtcars %>%
freq_table(am, vs) %>%
freq_test() %>%
select(row_var:n, percent_row, p_chi2_pearson)
#> # A tibble: 4 × 7
#> row_var row_cat col_var col_cat n percent_row p_chi2_pearson
#> <chr> <chr> <chr> <chr> <int> <dbl> <dbl>
#> 1 am 0 vs 0 12 63.2 0.341
#> 2 am 0 vs 1 7 36.8 0.341
#> 3 am 1 vs 0 6 46.2 0.341
#> 4 am 1 vs 1 7 53.8 0.341You can learn more about the freq_table() function and ways to adjust
default behaviors in vignette(“using_freq_test”).
The freq_format function is intended to make it quick and easy to format the output of the freq_table function for tables that may be used for publication. For example, a proportion and 95% confidence interval could be formatted as “24.00 (21.00 - 27.00).”
mtcars %>%
freq_table(am) %>%
freq_format(
recipe = "percent (lcl - ucl)",
name = "percent_95",
digits = 2
) %>%
select(var, cat, percent_95)
#> var cat percent_95
#> 1 am 0 59.38 (40.94 - 75.50)
#> 2 am 1 40.62 (24.50 - 59.06)You can learn more about the freq_format() function by reading the
function documentation.
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