R: Grouped histograms for distribution of a labeled numeric...

grouped_ggdotplotstats {ggstatsplot}

R Documentation

Grouped histograms for distribution of a labeled numeric variable

Description

Helper function for ggstatsplot::ggdotplotstats to apply this function across multiple levels of a given factor and combining the resulting plots using ggstatsplot::combine_plots.

Usage

grouped_ggdotplotstats(
  data,
  ...,
  grouping.var,
  plotgrid.args = list(),
  annotation.args = list()
)

Arguments

`data`	A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix,table, array, etc.) will not be accepted. Additionally, grouped data frames from `{dplyr}` should be ungrouped before they are entered as `data`.
`...`	Arguments passed on to `ggdotplotstats` `y` Label or grouping variable. `point.args` A list of additional aesthetic arguments passed to `geom_point`. `centrality.line.args` A list of additional aesthetic arguments to be passed to the `geom_line` used to display the lines corresponding to the centrality parameter. `x` A numeric variable from the data frame `data`. `type` A character specifying the type of statistical approach: `"parametric"` `"nonparametric"` `"robust"` `"bayes"` You can specify just the initial letter. `test.value` A number indicating the true value of the mean (Default: `0`). `digits` Number of digits for rounding or significant figures. May also be `"signif"` to return significant figures or `"scientific"` to return scientific notation. Control the number of digits by adding the value as suffix, e.g. `digits = "scientific4"` to have scientific notation with 4 decimal places, or `digits = "signif5"` for 5 significant figures (see also `signif()`). `conf.level` Scalar between `0` and `1` (default: `⁠95%⁠` confidence/credible intervals, `0.95`). If `NULL`, no confidence intervals will be computed. `tr` Trim level for the mean when carrying out `robust` tests. In case of an error, try reducing the value of `tr`, which is by default set to `0.2`. Lowering the value might help. `bf.prior` A number between `0.5` and `2` (default `0.707`), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: `"medium"`, `"wide"`, and `"ultrawide"`, corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects. `effsize.type` Type of effect size needed for parametric tests. The argument can be `"d"` (for Cohen's d) or `"g"` (for Hedge's g). `xlab` Label for `x` axis variable. If `NULL` (default), variable name for `x` will be used. `bf.message` Logical that decides whether to display Bayes Factor in favor of the null hypothesis. This argument is relevant only for parametric test (Default: `TRUE`). `results.subtitle` Decides whether the results of statistical tests are to be displayed as a subtitle (Default: `TRUE`). If set to `FALSE`, only the plot will be returned. `subtitle` The text for the plot subtitle. Will work only if `results.subtitle = FALSE`. `caption` The text for the plot caption. This argument is relevant only if `bf.message = FALSE`. `centrality.plotting` Logical that decides whether centrality tendency measure is to be displayed as a point with a label (Default: `TRUE`). Function decides which central tendency measure to show depending on the `type` argument. mean for parametric statistics median for non-parametric statistics trimmed mean for robust statistics MAP estimator for Bayesian statistics If you want default centrality parameter, you can specify this using `centrality.type` argument. `centrality.type` Decides which centrality parameter is to be displayed. The default is to choose the same as `type` argument. You can specify this to be: `"parameteric"` (for mean) `"nonparametric"` (for median) `robust` (for trimmed mean) `bayes` (for MAP estimator) Just as `type` argument, abbreviations are also accepted. `ggplot.component` A `ggplot` component to be added to the plot prepared by `{ggstatsplot}`. This argument is primarily helpful for `grouped_` variants of all primary functions. Default is `NULL`. The argument should be entered as a `{ggplot2}` function or a list of `{ggplot2}` functions. `ggtheme` A `{ggplot2}` theme. Default value is `ggstatsplot::theme_ggstatsplot()`. Any of the `{ggplot2}` themes (e.g., `theme_bw()`), or themes from extension packages are allowed (e.g., `ggthemes::theme_fivethirtyeight()`, `hrbrthemes::theme_ipsum_ps()`, etc.). But note that sometimes these themes will remove some of the details that `{ggstatsplot}` plots typically contains. For example, if relevant, `ggbetweenstats()` shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. `ggthemes::theme_fivethirtyeight()`) will remove the secondary Y-axis and thus the details as well. `ylab` Labels for `y` axis variable. If `NULL` (default), variable name for `y` will be used.
`grouping.var`	A single grouping variable.
`plotgrid.args`	A `list` of additional arguments passed to `patchwork::wrap_plots()`, except for `guides` argument which is already separately specified here.
`annotation.args`	A `list` of additional arguments passed to `patchwork::plot_annotation()`.

Details

For details, see: https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggdotplotstats.html

Examples


# for reproducibility
set.seed(123)
library(dplyr, warn.conflicts = FALSE)

# removing factor level with very few no. of observations
df <- filter(ggplot2::mpg, cyl %in% c("4", "6", "8"))

# plot
grouped_ggdotplotstats(
  data         = df,
  x            = cty,
  y            = manufacturer,
  grouping.var = cyl,
  test.value   = 15.5
)