Maturing lifecycle

Helper function for ggstatsplot::gghistostats to apply this function across multiple levels of a given factor and combining the resulting plots using ggstatsplot::combine_plots2.

grouped_gghistostats(
  data,
  x,
  grouping.var,
  binwidth = NULL,
  title.prefix = NULL,
  output = "plot",
  ...,
  plotgrid.args = list(),
  title.text = NULL,
  title.args = list(size = 16, fontface = "bold"),
  caption.text = NULL,
  caption.args = list(size = 10),
  sub.text = NULL,
  sub.args = list(size = 12)
)

Arguments

data

A dataframe (or a tibble) from which variables specified are to be taken. A matrix or tables will not be accepted.

x

A numeric variable from the dataframe data.

grouping.var

A single grouping variable (can be entered either as a bare name x or as a string "x").

binwidth

The width of the histogram bins. Can be specified as a numeric value, or a function that calculates width from x. The default is to use the max(x) - min(x) / sqrt(N). You should always check this value and explore multiple widths to find the best to illustrate the stories in your data.

title.prefix

Character string specifying the prefix text for the fixed plot title (name of each factor level) (Default: NULL). If NULL, the variable name entered for grouping.var will be used.

output

If "expression", will return expression with statistical details, while "dataframe" will return a dataframe containing the results.

...

Arguments passed on to gghistostats

normal.curve

A logical value that decides whether to super-impose a normal curve using stats::dnorm(mean(x), sd(x)). Default is FALSE.

normal.curve.args

A list of additional aesthetic arguments to be passed to the normal curve.

bar.fill

Character input that decides which color will uniformly fill all the bars in the histogram (Default: "grey50").

type

Type of statistic expected ("parametric" or "nonparametric" or "robust" or "bayes").Corresponding abbreviations are also accepted: "p" (for parametric), "np" (nonparametric), "r" (robust), or "bf"resp.

test.value

A number specifying the value of the null hypothesis (Default: 0).

bf.prior

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors.

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).

conf.level

Scalar between 0 and 1. If unspecified, the defaults return 95% confidence/credible intervals (0.95).

nboot

Number of bootstrap samples for computing confidence interval for the effect size (Default: 100).

tr

Trim level for the mean when carrying out robust tests. If you get error stating "Standard error cannot be computed because of Winsorized variance of 0 (e.g., due to ties). Try to decrease the trimming level.", try to play around with the value of tr, which is by default set to 0.1. Lowering the value might help.

k

Number of digits after decimal point (should be an integer) (Default: k = 2L).

centrality.k

Integer denoting the number of decimal places expected for centrality parameter label. (Default: 2L).

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 and test value.

centrality.label.args

A list of additional aesthetic arguments to be passed to the geom_label used to display the label corresponding to the centrality parameter and test value.

xlab

Labels for x and y axis variables. If NULL (default), variable names for x and y will be used.

subtitle

The text for the plot subtitle. Will work only if results.subtitle = FALSE.

caption

The text for the plot caption.

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).

ggtheme

A function, ggplot2 theme name. Default value is ggplot2::theme_bw(). Any of the ggplot2 themes, or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.).

ggstatsplot.layer

Logical that decides whether theme_ggstatsplot theme elements are to be displayed along with the selected ggtheme (Default: TRUE). theme_ggstatsplot is an opinionated theme layer that override some aspects of the selected ggtheme.

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.

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, median for non-parametric, trimmed mean for robust, and MAP estimator for Bayes).

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.

plotgrid.args

A list of additional arguments to cowplot::plot_grid.

title.text

String or plotmath expression to be drawn as title for the combined plot.

title.args

A list of additional arguments provided to title, caption and sub, resp.

caption.text

String or plotmath expression to be drawn as the caption for the combined plot.

caption.args

A list of additional arguments provided to title, caption and sub, resp.

sub.text

The label with which the combined plot should be annotated. Can be a plotmath expression.

sub.args

A list of additional arguments provided to title, caption and sub, resp.

References

https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/gghistostats.html

See also

Examples

# \donttest{ # for reproducibility set.seed(123) # plot ggstatsplot::grouped_gghistostats( data = iris, x = Sepal.Length, test.value = 5, grouping.var = Species, bar.fill = "orange", ggplot.component = list( ggplot2::scale_x_continuous(breaks = seq(3, 9, 1), limits = (c(3, 9))), ggplot2::scale_y_continuous(breaks = seq(0, 25, 5), limits = (c(0, 25))) ), plotgrid.args = list(nrow = 1, labels = c("(i)", "(ii)", "(iii)")), )
#> Scale for 'y' is already present. Adding another scale for 'y', which will #> replace the existing scale.
#> Scale for 'y' is already present. Adding another scale for 'y', which will #> replace the existing scale.
#> t is large; approximation invoked.
#> Scale for 'y' is already present. Adding another scale for 'y', which will #> replace the existing scale.
# }