grouped_ggbetweenstats

From ggstatsplot v0.1.4 by Indrajeet Patil
0th

Percentile

Violin plots for group or condition comparisons in between-subjects designs repeated across all levels of a grouping variable.

A combined plot of comparison plot created for levels of a grouping variable.

Usage
grouped_ggbetweenstats(
  data,
  x,
  y,
  grouping.var,
  title.prefix = NULL,
  plot.type = "boxviolin",
  type = "parametric",
  pairwise.comparisons = FALSE,
  pairwise.annotation = "p.value",
  pairwise.display = "significant",
  p.adjust.method = "holm",
  effsize.type = "unbiased",
  partial = TRUE,
  effsize.noncentral = TRUE,
  bf.prior = 0.707,
  bf.message = TRUE,
  results.subtitle = TRUE,
  xlab = NULL,
  ylab = NULL,
  subtitle = NULL,
  stat.title = NULL,
  caption = NULL,
  sample.size.label = TRUE,
  k = 2,
  var.equal = FALSE,
  conf.level = 0.95,
  nboot = 100,
  tr = 0.1,
  sort = "none",
  sort.fun = mean,
  axes.range.restrict = FALSE,
  mean.label.size = 3,
  mean.label.fontface = "bold",
  mean.label.color = "black",
  notch = FALSE,
  notchwidth = 0.5,
  linetype = "solid",
  outlier.tagging = FALSE,
  outlier.label = NULL,
  outlier.label.color = "black",
  outlier.color = "black",
  outlier.shape = 19,
  outlier.coef = 1.5,
  mean.plotting = TRUE,
  mean.ci = FALSE,
  mean.size = 5,
  mean.color = "darkred",
  point.jitter.width = NULL,
  point.jitter.height = 0,
  point.dodge.width = 0.6,
  ggtheme = ggplot2::theme_bw(),
  ggstatsplot.layer = TRUE,
  package = "RColorBrewer",
  palette = "Dark2",
  direction = 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

The grouping variable from the dataframe data.

y

The response (a.k.a. outcome or dependent) 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").

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.

plot.type

Character describing the type of plot. Currently supported plots are "box" (for pure boxplots), "violin" (for pure violin plots), and "boxviolin" (for a combination of box and violin plots; default).

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.

pairwise.comparisons

Logical that decides whether pairwise comparisons are to be displayed (default: FALSE). Please note that only significant comparisons will be shown by default. To change this behavior, select appropriate option with pairwise.display argument.

pairwise.annotation

Character that decides the annotations to use for pairwise comparisons. Either "p.value" (default) or "asterisk".

pairwise.display

Decides which pairwise comparisons to display. Available options are "significant" (abbreviation accepted: "s") or "non-significant" (abbreviation accepted: "ns") or "everything"/"all". The default is "significant". You can use this argument to make sure that your plot is not uber-cluttered when you have multiple groups being compared and scores of pairwise comparisons being displayed.

p.adjust.method

Adjustment method for p-values for multiple comparisons. Possible methods are: "holm" (default), "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none".

effsize.type

Type of effect size needed for parametric tests. The argument can be "biased" (equivalent to "d" for Cohen's d for t-test; "partial_eta" for partial eta-squared for anova) or "unbiased" (equivalent to "g" Hedge's g for t-test; "partial_omega" for partial omega-squared for anova)).

partial

Logical that decides if partial eta-squared or omega-squared are returned (Default: TRUE). If FALSE, eta-squared or omega-squared will be returned. Valid only for objects of class lm, aov, anova, or aovlist.

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).

bf.prior

A number 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).

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.

xlab

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

ylab

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.

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: ".

caption

The text for the plot caption.

sample.size.label

Logical that decides whether sample size information should be displayed for each level of the grouping variable x (Default: TRUE).

k

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

var.equal

a logical variable indicating whether to treat the variances in the samples as equal. If TRUE, then a simple F test for the equality of means in a one-way analysis of variance is performed. If FALSE, an approximate method of Welch (1951) is used, which generalizes the commonly known 2-sample Welch test to the case of arbitrarily many samples.

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).

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.

sort

If "ascending" (default), x-axis variable factor levels will be sorted based on increasing values of y-axis variable. If "descending", the opposite. If "none", no sorting will happen.

sort.fun

The function used to sort (default: mean).

axes.range.restrict

Logical that decides whether to restrict the axes values ranges to min and max values of the axes variables (Default: FALSE), only relevant for functions where axes variables are of numeric type.

mean.label.size

Aesthetics for the label displaying mean. Defaults: 3, "bold","black", respectively.

mean.label.fontface

Aesthetics for the label displaying mean. Defaults: 3, "bold","black", respectively.

mean.label.color

Aesthetics for the label displaying mean. Defaults: 3, "bold","black", respectively.

notch

A logical. If FALSE (default), a standard box plot will be displayed. If TRUE, a notched box plot will be used. Notches are used to compare groups; if the notches of two boxes do not overlap, this suggests that the medians are significantly different. In a notched box plot, the notches extend 1.58 * IQR / sqrt(n). This gives a roughly 95% confidence interval for comparing medians. IQR: Inter-Quartile Range.

notchwidth

For a notched box plot, width of the notch relative to the body (default 0.5).

linetype

Character strings ("blank", "solid", "dashed", "dotted", "dotdash", "longdash", and "twodash") specifying the type of line to draw box plots (Default: "solid"). Alternatively, the numbers 0 to 6 can be used (0 for "blank", 1 for "solid", etc.).

outlier.tagging

Decides whether outliers should be tagged (Default: FALSE).

outlier.label

Label to put on the outliers that have been tagged. This can't be the same as x argument.

outlier.label.color

Color for the label to to put on the outliers that have been tagged (Default: "black").

outlier.color

Default aesthetics for outliers (Default: "black").

outlier.shape

Hiding the outliers can be achieved by setting outlier.shape = NA. Importantly, this does not remove the outliers, it only hides them, so the range calculated for the y-axis will be the same with outliers shown and outliers hidden.

outlier.coef

Coefficient for outlier detection using Tukey's method. With Tukey's method, outliers are below (1st Quartile) or above (3rd Quartile) outlier.coef times the Inter-Quartile Range (IQR) (Default: 1.5).

mean.plotting

Logical that decides whether mean is to be highlighted and its value to be displayed (Default: TRUE).

mean.ci

Logical that decides whether 95% confidence interval for mean is to be displayed (Default: FALSE).

mean.size

Point size for the data point corresponding to mean (Default: 5).

mean.color

Color for the data point corresponding to mean (Default: "darkred").

point.jitter.width

Numeric specifying the degree of jitter in x direction. Defaults to 40% of the resolution of the data.

point.jitter.height

Numeric specifying the degree of jitter in y direction. Defaults to 0.1.

point.dodge.width

Numeric specifying the amount to dodge in the x direction. Defaults to 0.60.

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.

package

Name of package from which the palette is desired as string or symbol.

palette

Name of palette as string or symbol.

direction

Either 1 or -1. If -1 the palette will be reversed.

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).

...

Arguments passed on to combine_plots

title.text

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

title.color

Text color for title.

title.size

Point size of title text.

title.vjust

Vertical justification for title. Default = 0.5 (centered on y). 0 = baseline at y, 1 = ascender at y.

title.hjust

Horizontal justification for title. Default = 0.5 (centered on x). 0 = flush-left at x, 1 = flush-right.

title.fontface

The font face ("plain", "bold" (default), "italic", "bold.italic") for title.

caption.text

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

caption.color

Text color for caption.

caption.size

Point size of title text.

caption.vjust

Vertical justification for caption. Default = 0.5 (centered on y). 0 = baseline at y, 1 = ascender at y.

caption.hjust

Horizontal justification for caption. Default = 0.5 (centered on x). 0 = flush-left at x, 1 = flush-right.

caption.fontface

The font face ("plain" (default), "bold", "italic", "bold.italic") for caption.

sub.text

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

sub.color

Text color for annotation label (Default: "black").

sub.size

Point size of annotation text (Default: 12).

sub.x

The x position of annotation label (Default: 0.5).

sub.y

The y position of annotation label (Default: 0.5).

sub.hjust

Horizontal justification for annotation label (Default: 0.5).

sub.vjust

Vertical justification for annotation label (Default: 0.5).

sub.vpadding

Vertical padding. The total vertical space added to the label, given in grid units. By default, this is added equally above and below the label. However, by changing the y and vjust parameters, this can be changed (Default: ggplot2::unit(1, "lines")).

sub.fontface

The font face ("plain" (default), "bold", "italic", "bold.italic") for the annotation label.

sub.angle

Angle at which annotation label is to be drawn (Default: 0).

sub.lineheight

Line height of annotation label.

title.caption.rel.heights

Numerical vector of relative columns heights while combining (title, plot, caption).

title.rel.heights

Numerical vector of relative columns heights while combining (title, plot).

caption.rel.heights

Numerical vector of relative columns heights while combining (plot, caption).

Details

For parametric tests, Welch's ANOVA/t-test are used as a default (i.e., var.equal = FALSE). References:

  • ANOVA: Delacre, Leys, Mora, & Lakens, PsyArXiv, 2018

  • t-test: Delacre, Lakens, & Leys, International Review of Social Psychology, 2017

If robust tests are selected, following tests are used is .

  • ANOVA: one-way ANOVA on trimmed means (see ?WRS2::t1way)

  • t-test: Yuen's test for trimmed means (see ?WRS2::yuen)

For more about how the effect size measures (for nonparametric tests) and their confidence intervals are computed, see ?rcompanion::wilcoxonR.

For repeated measures designs, use ggwithinstats.

References

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

See Also

ggbetweenstats, ggwithinstats, grouped_ggwithinstats

Aliases
  • grouped_ggbetweenstats
Examples
# NOT RUN {
# to get reproducible results from bootstrapping
set.seed(123)

# the most basic function call
ggstatsplot::grouped_ggbetweenstats(
  data = dplyr::filter(ggplot2::mpg, drv != "4"),
  x = year,
  y = hwy,
  grouping.var = drv,
  conf.level = 0.99
)

# modifying individual plots using `ggplot.component` argument
ggstatsplot::grouped_ggbetweenstats(
  data = dplyr::filter(
    ggstatsplot::movies_long,
    genre %in% c("Action", "Comedy"),
    mpaa %in% c("R", "PG")
  ),
  x = genre,
  y = rating,
  grouping.var = mpaa,
  results.subtitle = FALSE,
  ggplot.component = ggplot2::scale_y_continuous(
    breaks = seq(1, 9, 1),
    limits = (c(1, 9))
  ),
  messages = FALSE
)
# }
Documentation reproduced from package ggstatsplot, version 0.1.4, License: GPL-3 | file LICENSE

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