Histogram with statistical details from one-sample test included in the plot as a subtitle.

gghistostats(data, x, binwidth = NULL, bar.measure = "count",
  xlab = NULL, stat.title = NULL, title = NULL, subtitle = NULL,
  caption = NULL, type = "parametric", test.value = 0,
  bf.prior = 0.707, bf.message = TRUE, robust.estimator = "onestep",
  effsize.type = "g", effsize.noncentral = TRUE, conf.level = 0.95,
  nboot = 100, k = 2, ggtheme = ggplot2::theme_bw(),
  ggstatsplot.layer = TRUE, fill.gradient = FALSE,
  low.color = "#0072B2", high.color = "#D55E00", bar.fill = "grey50",
  results.subtitle = TRUE, centrality.para = "mean",
  centrality.color = "blue", centrality.size = 1,
  centrality.linetype = "dashed", centrality.line.labeller = TRUE,
  centrality.k = 2, test.value.line = FALSE,
  test.value.color = "black", test.value.size = 1,
  test.value.linetype = "dashed", test.line.labeller = TRUE,
  test.k = 0, normal.curve = FALSE, normal.curve.color = "black",
  normal.curve.linetype = "solid", normal.curve.size = 1,
  ggplot.component = NULL, return = "plot", messages = TRUE)

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.

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.

bar.measure

Character describing what value needs to be represented as height in the bar chart. This can either be "count", which shows number of points in bin, or "density", which density of points in bin, scaled to integrate to 1, or "proportion", which shows relative frequencies of observations in each bin, or "mix", which shows both count and proportion in the same plot.

xlab

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

stat.title

A character describing the test being run, which will be added as a prefix in the subtitle. The default is NULL. An example of a stat.title argument will be something like "Student's t-test: ".

title

The text for the plot title.

subtitle

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

caption

The text for the plot caption.

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 numeric value between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes Factors.

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).

robust.estimator

If type = "robust", a robust estimator to be used ("onestep" (Default), "mom", or "median"). For more, see ?WRS2::onesampb.

effsize.type

Type of effect size needed for parametric tests. The argument can be "biased" ("d" for Cohen's d) or "unbiased" ("g" Hedge's g for t-test). The default is "g".

effsize.noncentral

Logical indicating whether to use non-central t-distributions for computing the confidence interval for Cohen's d or Hedge's g (Default: TRUE).

conf.level

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

nboot

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

k

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

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.

fill.gradient

Logical decides whether color fill gradient is to be displayed (Default: FALSE). If FALSE, the legend and the color gradient will also be removed. The default is set to FALSE because the gradient provides redundant information in light of y-axis labels.

low.color, high.color

Colors for low and high ends of the gradient. Defaults are colorblind-friendly.

bar.fill

If fill.gradient = FALSE, then bar.fill decides which color will uniformly fill all the bars in the histogram (Default: "grey50").

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.para

Decides which measure of central tendency ("mean" or "median") is to be displayed as a vertical line.

centrality.color

Decides color for the vertical line for centrality parameter (Default: "blue").

centrality.size

Decides size for the vertical line for centrality parameter (Default: 1.2).

centrality.linetype

Decides linetype for the vertical line for centrality parameter (Default: "dashed").

centrality.line.labeller

A logical that decides whether line labels should be displayed for the centrality.para line (Default: TRUE).

centrality.k

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

test.value.line

Decides whether test value is to be displayed as a vertical line (Default: FALSE).

test.value.color

Decides color for the vertical line denoting test value (Default: "black").

test.value.size

Decides size for the vertical line for test value (Default: 1.2).

test.value.linetype

Decides linetype for the vertical line for test value (Default: "dashed").

test.line.labeller

A logical that decides whether line labels should be displayed for test.value line (Default: TRUE).

test.k

Integer denoting the number of decimal places expected for test.value label. (Default: 0 ).

normal.curve

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

normal.curve.color, normal.curve.linetype, normal.curve.size

If normal.curve = TRUE, then these arguments can be used to modify color (Default: "black"), size (default: 1.0), linetype (default: "solid").

ggplot.component

A ggplot component to be added to the plot prepared by ggstatsplot. This argument is primarily helpful for grouped_ variant of the current function. Default is NULL. The argument should be entered as a function. If the given function has an argument axes.range.restrict and if it has been set to TRUE, the added ggplot component might not work as expected.

return

Character that describes what is to be returned: can be "plot" (default) or "subtitle" or "caption". Setting this to "subtitle" will return the expression containing statistical results. If you have set results.subtitle = FALSE, then this will return a NULL. Setting this to "caption" will return the expression containing details about Bayes Factor analysis, but valid only when type = "parametric" and bf.message = TRUE, otherwise this will return a NULL.

messages

Decides whether messages references, notes, and warnings are to be displayed (Default: TRUE).

References

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

See also

Examples

# most basic function call with the defaults # this is the **only** function where data argument can be `NULL` ggstatsplot::gghistostats( data = ToothGrowth, x = len, xlab = "Tooth length", centrality.para = "median" )
#> t is large; approximation invoked.
#> Warning: full precision may not have been achieved in 'pnt{final}'
#> Warning: full precision may not have been achieved in 'pnt{final}'
#> Note: Shapiro-Wilk Normality Test for Tooth length: p-value = 0.109
#>
# a detailed function call ggstatsplot::gghistostats( data = iris, x = Sepal.Length, bar.measure = "mix", type = "p", caption = substitute(paste(italic("Note"), ": Iris dataset by Fisher.")), bf.prior = 0.8, test.value = 3, test.value.line = TRUE, binwidth = 0.10, bar.fill = "grey50" )
#> t is large; approximation invoked.
#> Warning: full precision may not have been achieved in 'pnt{final}'
#> Warning: full precision may not have been achieved in 'pnt{final}'
#> Warning: full precision may not have been achieved in 'pnt{final}'
#> Note: Shapiro-Wilk Normality Test for Sepal.Length: p-value = 0.010
#>