The goal of meantables is to quickly make tables of descriptive statistics (i.e., counts, means, confidence intervals) for continuous variables. 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 meantables from CRAN with:
install.packages("meantables")
And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("brad-cannell/meantables")
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(meantables)
data("mtcars")
mtcars %>%
mean_table(mpg)
#> # A tibble: 1 × 9
#> response_var n mean sd sem lcl ucl min max
#> <chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 mpg 32 20.1 6.03 1.07 17.9 22.3 10.4 33.9
mtcars %>%
mean_table(mpg) %>%
mean_format(
recipe = "mean (lcl - ucl)",
name = "mean_95",
digits = 1
) %>%
select(response_var, mean_95)
#> # A tibble: 1 × 2
#> response_var mean_95
#> <chr> <chr>
#> 1 mpg 20.1 (17.9 - 22.3)
mtcars %>%
group_by(cyl) %>%
mean_table(mpg) %>%
mean_format("mean (sd)") %>%
select(response_var:group_cat, formatted_stats)
#> # A tibble: 3 × 4
#> response_var group_var group_cat formatted_stats
#> <chr> <chr> <dbl> <chr>
#> 1 mpg cyl 4 26.66 (4.51)
#> 2 mpg cyl 6 19.74 (1.45)
#> 3 mpg cyl 8 15.1 (2.56)
mtcars %>%
group_by(cyl) %>%
mean_table(mpg)
#> # A tibble: 3 × 11
#> response_var group_var group…¹ n mean sd sem lcl ucl min max
#> <chr> <chr> <dbl> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 mpg cyl 4 11 26.7 4.51 1.36 23.6 29.7 21.4 33.9
#> 2 mpg cyl 6 7 19.7 1.45 0.549 18.4 21.1 17.8 21.4
#> 3 mpg cyl 8 14 15.1 2.56 0.684 13.6 16.6 10.4 19.2
#> # … with abbreviated variable name ¹group_cat