About

This shows examples of plotting group differences using GG_group_means() in kirkegaard package. These are all based on ggplot2.

Init

Packages and options.

#options
options(digits = 2,
        tibble.print_max = 30)

#packages
library(pacman)
p_load(kirkegaard)

#default theme
theme_set(theme_bw())

Examples

#simple examples
#default
GG_group_means(iris, "Sepal.Length", "Species")

#just a single point, not tied to 0 (for non-ratio data)
GG_group_means(iris, "Sepal.Length", "Species", type = "point")

#points
GG_group_means(iris, "Sepal.Length", "Species", type = "points")

#tighter CI
GG_group_means(iris, "Sepal.Length", "Species", type = "points", CI = .999)

#no CI
GG_group_means(iris, "Sepal.Length", "Species", type = "points", CI = NA)

#other plots
GG_group_means(iris, "Sepal.Length", "Species", type = "boxplot")

GG_group_means(iris, "Sepal.Length", "Species", type = "violin")

GG_group_means(iris, "Sepal.Length", "Species", type = "violin2")

#subgroups too
iris$type = sample(LETTERS[1:3], size = nrow(iris), replace = T)
GG_group_means(iris, var = "Sepal.Length", groupvar = "Species", subgroupvar = "type")

GG_group_means(iris, var = "Sepal.Length", groupvar = "Species", subgroupvar = "type", type = "point")

GG_group_means(iris, var = "Sepal.Length", groupvar = "Species", subgroupvar = "type", type = "points")

GG_group_means(iris, var = "Sepal.Length", groupvar = "Species", subgroupvar = "type", type = "boxplot")

GG_group_means(iris, var = "Sepal.Length", groupvar = "Species", subgroupvar = "type", type = "violin")

GG_group_means(iris, var = "Sepal.Length", groupvar = "Species", subgroupvar = "type", type = "violin2")

#proportions automate the use of proper proportional tests
iris$onezero = sample(c(0, 1), size = nrow(iris), replace = T)
GG_group_means(iris, "onezero", "Species")
## Proportion variable detected, using `prop.test()`

GG_group_means(iris, "onezero", "Species", subgroupvar = "type")
## Proportion variable detected, using `prop.test()`
## Warning in prop.test(sum(dd[[var]] == 1), length(dd[[var]])): Chi-squared
## approximation may be incorrect