Helper function for ggstatsplot::ggpiestats
to apply this
function across multiple levels of a given factor and combining the
resulting plots using ggstatsplot::combine_plots
.
grouped_ggpiestats(
data,
main,
condition = NULL,
counts = NULL,
grouping.var,
title.prefix = NULL,
output = "plot",
x = NULL,
y = NULL,
...,
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)
)
A dataframe (or a tibble) from which variables specified are to be taken. A matrix or tables will not be accepted.
The variable to use as the rows in the contingency table.
The variable to use as the columns in the contingency
table. Default is NULL
. If NULL
, one-sample proportion test (a goodness
of fit test) will be run for the x
variable. Otherwise an appropriate
association test will be run. This argument can not be NULL
for
ggbarstats
function.
A string naming a variable in data containing counts, or NULL
if each row represents a single observation (Default).
A single grouping variable (can be entered either as a
bare name x
or as a string "x"
).
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.
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
. For functions
ggpiestats
and ggbarstats
, setting output = "proptest"
will return a
dataframe containing results from proportion tests.
The variable to use as the rows in the contingency table.
The variable to use as the columns in the contingency
table. Default is NULL
. If NULL
, one-sample proportion test (a goodness
of fit test) will be run for the x
variable. Otherwise an appropriate
association test will be run. This argument can not be NULL
for
ggbarstats
function.
Arguments passed on to ggpiestats
proportion.test
Decides whether proportion test for main
variable is
to be carried out for each level of condition
(Default: TRUE
).
perc.k
Numeric that decides number of decimal places for percentage
labels (Default: 0
).
label
Character decides what information needs to be displayed
on the label in each pie slice. Possible options are "percentage"
(default), "counts"
, "both"
.
label.args
Additional aesthetic arguments that will be passed to
geom_label
.
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.
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
).
subtitle
The text for the plot subtitle. Will work only if
results.subtitle = FALSE
.
caption
The text for the plot caption.
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
.
package
Name of package from which the palette is desired as string or symbol.
palette
Name of palette as string or symbol.
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.
messages
Decides whether messages references, notes, and warnings are
to be displayed (Default: TRUE
).
ratio
A vector of proportions: the expected proportions for the
proportion test (should sum to 1). Default is NULL
, which means the null
is equal theoretical proportions across the levels of the nominal variable.
This means if there are two levels this will be ratio = c(0.5,0.5)
or if
there are four levels this will be ratio = c(0.25,0.25,0.25,0.25)
, etc.
sampling.plan
Character describing the sampling plan. Possible options
are "indepMulti"
(independent multinomial; default), "poisson"
,
"jointMulti"
(joint multinomial), "hypergeom"
(hypergeometric). For
more, see ?BayesFactor::contingencyTableBF()
.
fixed.margin
For the independent multinomial sampling plan, which
margin is fixed ("rows"
or "cols"
). Defaults to "rows"
.
prior.concentration
Specifies the prior concentration parameter, set
to 1
by default. It indexes the expected deviation from the null
hypothesis under the alternative, and corresponds to Gunel and Dickey's
(1974) "a"
parameter.
paired
Logical indicating whether data came from a within-subjects or
repeated measures design study (Default: FALSE
). If TRUE
, McNemar's
test subtitle will be returned. If FALSE
, Pearson's chi-square test will
be returned.
legend.title
Title text for the legend.
A list of additional arguments to cowplot::plot_grid
.
String or plotmath expression to be drawn as title for the combined plot.
A list of additional arguments
provided to title
, caption
and sub
, resp.
String or plotmath expression to be drawn as the caption for the combined plot.
A list of additional arguments
provided to title
, caption
and sub
, resp.
The label with which the combined plot should be annotated. Can be a plotmath expression.
A list of additional arguments
provided to title
, caption
and sub
, resp.
Unlike a number of statistical softwares, ggstatsplot
doesn't
provide the option for Yates' correction for the Pearson's chi-squared
statistic. This is due to compelling amount of Monte-Carlo simulation
research which suggests that the Yates' correction is overly conservative,
even in small sample sizes. As such it is recommended that it should not
ever be applied in practice (Camilli & Hopkins, 1978, 1979; Feinberg, 1980;
Larntz, 1978; Thompson, 1988).
For more about how the effect size measures and their confidence intervals
are computed, see ?rcompanion::cohenG
, ?rcompanion::cramerV
, and
?rcompanion::cramerVFit
.
https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggpiestats.html
# NOT RUN {
# grouped one-sample proportion tests
ggstatsplot::grouped_ggpiestats(
data = mtcars,
grouping.var = am,
x = cyl
)
# the following will take slightly more amount of time
# for reproducibility
set.seed(123)
# let's create a smaller dataframe
diamonds_short <- ggplot2::diamonds %>%
dplyr::filter(.data = ., cut %in% c("Fair", "Very Good", "Ideal")) %>%
dplyr::sample_frac(tbl = ., size = 0.10)
# plot
ggstatsplot::grouped_ggpiestats(
data = diamonds_short,
x = color,
y = clarity,
grouping.var = cut,
nboot = 20,
sampling.plan = "poisson",
title.prefix = "Quality",
slice.label = "both",
messages = FALSE,
perc.k = 1,
plotgrid.args = list(nrow = 3)
)
# }
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