ggbarstats() (and grouped_ggbarstats()) now supports one-sample
goodness-of-fit tests when only x is specified (with y = NULL as the new
default). This produces a single stacked bar chart with chi-squared GOF test
results in the subtitle, mirroring the existing one-sample support in
ggpiestats() (#532, #697).
ggpiestats() and ggbarstats() now compute pairwise contingency table
analyses (Fisher's exact tests via pairwise_contingency_table()) when x
has more than two levels. These are available via
extract_stats(plot)$pairwise_comparisons_data. A new p.adjust.method
parameter controls the p-value adjustment method (default: "holm").
Pairwise results are not displayed on the plots since bar and pie charts lack
a natural visual representation for pairwise significance annotations (#554).
ggscatterstats() now sets a default number of bins for marginal
histograms, suppressing the stat_bin() message about picking a better
binwidth (#810).
ggscatterstats() gains xsidehistogram.scale and ysidehistogram.scale
parameters to control the scale (e.g., breaks, limits, transform) of
the marginal distribution histograms (#898).
All top-level plotting functions now include an alternative argument, which
is passed down to {statsExpressions} to specify the alternative hypothesis for
effect size confidence intervals (#794).
ggbetweenstats() and ggwithinstats() now include a pairwise.alpha
argument to control the alpha cutoff used for filtering displayed pairwise
comparisons, and the secondary-axis label now reports the chosen alpha.
The following expert-level statistical parameters have been removed from all function signatures because their defaults are the universally recommended values and changing them requires specialist knowledge (#1087):
var.equal (from ggbetweenstats()): Welch's test (var.equal = FALSE)
is uniformly recommended over Student's t-test.nboot (from ggbetweenstats(), ggwithinstats()): 100 bootstrap
resamples is adequate for trimmed-mean CIs.sampling.plan, fixed.margin, prior.concentration (from
ggpiestats(), ggbarstats()): Technical BayesFactor settings that
virtually no one changes.effsize.type (from ggbetweenstats(), ggwithinstats(),
gghistostats(), ggdotplotstats()): The unbiased effect size estimator
is now always used.Users who need non-default values for these parameters should call
{statsExpressions} directly.
ggwithinstats() (and grouped_ggwithinstats()) gains a subject.id
parameter. When provided, the subject identifier column is used to correctly
pair observations across conditions and to remove NA observations by subject
key rather than by positional row number. Plots and statistical results for
unsorted repeated-measures data will differ from previous versions once
subject.id is supplied. All examples and vignettes have been updated to
pass subject.id explicitly, which is now the recommended practice.
The package argument has been removed from all plotting functions. The
palette argument now accepts a single "package::palette" string (e.g.,
palette = "ggthemes::gdoc"), matching the convention used by
{paletteer} itself.
The default palette has been changed from "RColorBrewer::Dark2" (8
colors) to "ggthemes::gdoc" (24 qualitative colors), which accommodates
categorical variables with up to 24 levels without errors (#1015).
When the chosen palette does not have enough colors for the number of levels in the data, an error is now thrown (previously a warning was issued that was silently ignored until ggplot2 crashed anyway).
Grouped plot functions (e.g., grouped_ggbarstats()) now preserve the order
of groups as they appear in the data rather than sorting them alphabetically
(#792).
combine_plots() now renders the overall annotation title in bold by
default, matching the styling used for individual plot titles.
grouped_ggbarstats() and grouped_ggpiestats() now display a single
unified legend when different groups have different observed factor levels for
the x variable. Previously, patchwork could not merge the per-panel fill
scales, producing duplicate legends (#868).
ggbetweenstats() and ggwithinstats() now correctly display sample size
labels on the x-axis even when centrality.plotting = FALSE (#695).
ggcoefstats() now preserves the model term order in the default top-to-bottom
plot layout and in estimate-sorted displays, instead of showing terms in the
reverse order (#642).
ggcoefstats() no longer draws empty stats.labels boxes for model terms
whose label expression is absent, which affected mixed-model coefficient
plots such as the documented lmer() example.
{dplyr} (v1.2.0) and {purrr} (v1.2.1).N.B. All statistical analysis in {ggstatsplot} is carried out in
{statsExpressions}. Thus, to see changes related to statistical expressions,
read the NEWS for that package:
https://www.indrapatil.com/statsExpressions/news/index.html
DESCRIPTION. While Chuck
made significant contributions to early versions of the package (2018-2019),
all of his code was completely replaced during the 2019 refactoring when
statistical functionality was moved to the {statsExpressions} package.gghistostats() to fix parsing issues on secondary axis labels
due to changes in upstream dependencies.{ggplot2} release.The license for the package has been changed from GPL-3 to MIT.
ggdotplotstats() displays uncertainty (confidence intervals) for the
centrality measure estimates in the plot. This is controlled by the conf.int
argument. The default is TRUE, which means that the confidence intervals are
displayed. If you do not want to display them, set conf.int = FALSE.
R 4.3.{easystats} package updates.extract_stats() returns a list of class ggstatsplot_stats which contains
all the statistical summaries and expressions for a given plot.
extract_stats(), extract_subtitle(), extract_caption() now works out of
the box for the grouped plots as well.
ggpiestats() and ggbarstats() now respect ratio() argument for
proportion tests run in case of two-way contingency tables (#818).bugs_wide.gghistostats()) has been removed. This feature always felt like an ad hoc
addition to the plot, and has nothing to do with the key statistical analysis
in question (which is not about checking the normality of the distribution).ggpiestats() and
ggbarstats() (#935).The cryptic but very useful parameter k has been renamed to digits to
improve its discoverability.
To be consistent with other functions, ggpiestats() and ggbarstats() now
default to two-sided alternative hypothesis.
Maintenance updates for changes in upstream dependencies.
ggbarstats() gains sample.size.label.args parameter to pass additional
arguments to ggplot2::geom_text().
To be internally consistent, the plot.type argument has been removed from
ggbetweenstats(), since no such argument exists for ggwithinstats(). This
argument was also redundant. Since removing a specific geom is straightforward
using *.args arguments. Examples for these two functions illustrate how.
ggbetweenstats() and ggwithinstats() retire pairwise.comparisons
argument since it was redundant. In order to turn off showing pairwise
comparisons, you can now use pairwise.display = "none".
ggbetweenstats() gets boxplot.args argument to pass additional arguments
to the underlying geom function. This also fixes regression introduced in
0.11.1 release where outlier points were displayed along with box plot.ggbetweenstats() and ggwithinstats()
has been removed. It was too crude to be useful or reliable, and users should
instead prefer more informative methods (e.g.
performance::check_outliers()).{parameters}.R 4.1 because a crucial
dependency ({pbkrtest}) requires this R version.{ggplot2} and {easystats} updates.output parameter for all functions has been removed. All functions now
return only the plot, which itself contains all necessary details that were
previously extracted using the output argument. You can extract all the
necessary details (including expressions containing statistical details) from
a plot using extract_stats() function. There are two additional helpers to
get expressions: extract_subtitle() and extract_caption().xfill and yfill arguments for ggscatterstats() have been removed. You
can specify all aesthetic modifications for side histograms in scatter plot
using xsidehistogram.args and ysidehistogram.args arguments.
Updates to changes made in the latest {ggplot2} release (3.4.0).
Due to changes to the underlying API of {parameters}, the effsize argument
has been renamed to effectsize.type.
Removes unnecessary re-exports of {tidyverse} operators.
The pairwise_comparisons() function implementation now lives in
{statsExpressions} package, although it will continue to be exported from
{ggstatsplot} package.
ggbetweenstats() and ggwithinstats()
functions are now displayed as a label for the secondary axis. Previously,
this information was displayed in the caption. Given that caption already
contained Bayesian test details, it was becoming difficult to stack
different expressions on top of each other. To avoid unnecessary code
complexity and also to avoid crowded caption, this decision was made.
Additionally, the pairwise test label has been slightly abbreviated, and so
is the label for significance bars. This is done to not let the text
overwhelm the numeric values, the latter being more important.{PMCMRplus} package from Imports to Suggests. So, if, as a user, you
wish to use pairwise comparisons in ggbetweenstats() and
ggwithinstats(), you will need to download this package.pairwise_comparisons() function for carrying out one-way pairwise
comparisons has now moved in {ggstatsplot} from {pairwiseComparisons}
package.A number of effect size estimates and their confidence intervals have
changed due to respective changes made in {effectsize} package version
0.5 release. For full details of these changes, see:
https://easystats.github.io/effectsize/news/index.html
For plotting marginal distributions in ggscatterstats, {ggstatsplot} now
relies on {ggside} package instead of {ggExtra}. This was done to remove
a glaring inconsistency in the API. All functions in {ggstatsplot}
produced ggplot objects and could be further modified with ggplot2
functions, except ggscatterstats, which led to a lot of confusion among
users (e.g. #28). This change gets rid of this inconsistency. But it comes
at a cost: there is no more marginal.type argument that lets you change
the type of marginal distribution graphic and histogram is the only possible
option. Note that this is not a breaking change. Your past code will
continue to work but it will now always produce a histogram instead of other
marginal graphic you might have chosen.
4.0.Online vignette about combine_plots has been removed. In case you want to
create a grid of plots, it is highly recommended that you use patchwork
package directly and not this wrapper around it which is mostly useful with
{ggstatsplot} plots.
ggscatterstats labeling arguments accept only unquoted inputs now, and not
quoted or string inputs. Allowing this was a bad design choice in the past
since most functions in {ggstatsplot}, inspired by tidyverse, expect
unquoted (x) - and not quoted ("x") - arguments. So this function was
the odd one out.
Gets rid of ipmisc dependency.
Removes movies_wide dataset, which was virtually identical to
movies_long dataset and was not used anywhere in the package. Also removes
the unused VR_dilemma dataset.
extract_stats function to extract dataframes containing statistical
details.There is finally a publication for {ggstatsplot} package!
https://joss.theoj.org/papers/10.21105/joss.03167
The ggcoefstats function defaults to NULL for xlab and ylab
arguments, which lets users change these labels if they wish to do so.
Additionally, the x-axis label, if not specified, now defaults to
"estimate". Whether this estimate corresponds to regression coefficient or
effect size like partial eta-squared should be clear from the label itself.
To reduce the dependency load, ggcorrplot moves from Imports to
Suggests.
The bar.fill argument in gghistostats is retired in favor of the new
bin.args argument that can be used to pass aesthetic arguments to
ggplot2::stat_bin.
ggstatsplot.layer argument has been retired. If the user chooses a
certain ggplot2 theme, it means they want that theme, and not
{ggstatsplot}'s varnish on it. So the previous behavior was undesirable.
This is a backward compatible change, so the plots should not look
different.
The pch size for ggcorrmat has been increased to 14 (#579) to increase
its visibility compared to the correlation value text.
ggwithinstats gains point.args to change geom_point.
Minor change to ggcorrmat legend title - content in parentheses is now
shown outside of it.
ggcoefstats didn't work when statistic for the given model was
chi-squared. This has been fixed.To reduce the dependency load, ggExtra moves from Imports to
Suggests.
grouped_ functions (e.g., #559). The ggpiestats
and ggbarstats functions always behaved this way, but the rest of the
functions now also mimic this behavior.ggcoefstats labels do not contain degrees of freedom when they are not
available instead of displaying Inf.title.prefix is now
removed. It led to redundant title prefixes across different facets of the
plot. Given that grouped_ functions require users to set grouping.var,
it is fair to assume what variable the levels in the title correspond to.Adapts to changes made in statsExpressions 1.0.0.
sample.size.label argument is retired for ggbetweenstats,
ggwithinstats, and ggbarstats. I do not think it is ever a good idea to
not do this. If the users wish to not display sample sizes, they can easily
do this using scale_* functions from ggplot2.
In ggpiestats and ggbarstats, parametric proportion tests are now turned
off when type = "bayes".
combine_plots has been completely revised to rely not on patchwork, but
on patchwork, to combine a list of ggplot together. This was done to
have a leaner syntax. With this revision, its vestigial twin combine_plots
is no longer needed and has been removed. This should not break any of the
existing instances of grouped_ functions, although it will lead to changed
graphical layouts. The only instance in which this change will lead to a
breakage is when you specified labels argument. So, if you used
plotgrid.args = list(labels = "auto"), you will now have to replace it
with plotgrid.args = list(tag_level = "keep"). You can also use
annotation.args (e.g., annotation.args = list(tag_levels = "a") to
customize labels (this will create labels with pattern a, b, c, etc.).
Another instance of breakage is if you had used combine_plots function and
provided individual plots to ... instead as a list.
tr = 0.1 to tr = 0.2 (which is what WRS2 defaults
to).All robust tests in this package were based on trimmed means, except for
correlation test. This has been changed: the robust correlation measure is
now Winsorized correlation, which is based on trimming. Therefore, the
beta argument has been replaced by tr argument. This should result only
in minor changes in correlation coefficient estimates.
Using annotate instead of geom_label had significantly slowed down
gghistostats and ggdotplotstats functions. This has been fixed.
Removes the vestigial notch and notchwidth arguments for
ggbetweenstats and ggwithinstats.
All Bayesian expression templates are now explicit about the type of estimate being displayed.
For gghistostats and ggdotplotstats, the centrality measure labels used
to be attached to the vertical line, but this occluded the underlying data.
Now this label is instead shown on the top x-axis. Note that this means
that if you make any further changes to the resulting plot using the
ggplot2::scale_x_continuous function, this label will likely disappear.
The centrality.k argument is retired in favor of k.
More models supported in ggcoefstats: crr, eglm, elm, varest.
ggbetweenstats, ggwithinstats, gghistostats, ggdotplotstats gain
argument centrality.type that can be used to specify which centrality
parameter is to be displayed. So one can have type = "robust" and still
show median as centrality parameter by choosing centrality.type = "nonparametric".gghistostats removes bar.measure argument. The function now defaults to
showing the count information on the x-axis and the proportion
information on the duplicated x-axis.
ggscatterstats removes method and method.args arguments. It will no
longer be possible to use this function to visualize data for when the model
is not linear. It also retires margins argument.
For ggbetweenstats and ggwithinstats functions, the arguments of type
mean.* have all been replaced by centrality.*. This is because now these
functions decide 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).
Similarly, gghistostats and ggdotplotstats functions also decide 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). Therefore, centrality.parameter argument
has been removed. If you want to turn off displaying centrality measure, set
centrality.plotting = FALSE.
gghistostats and ggdotplotstats functions remove the functionality to
display a vertical line corresponding to test.value. This feature was
turned off by default in prior releases. Accordingly, all related arguments
from these two functions have been removed.
ggscatterstats defaults to densigram as the marginal distribution
visualization.
ggbetweenstats and ggwithinstats now display the centrality tendency
measure in such a way that the label doesn't occlude any of the raw data
points (#429).
mean.ci argument is retired for ggbetweenstats and ggwithinstats.
Future {ggstatsplot} releases will be providing different centrality
measures depending on the type argument and it is not guaranteed that all
of them will have CIs available. So, for the sake of consistency, this
argument is just going to be retired.
ggcorrmat uses pretty formatting to display sample size information.
ggcoefstats now also displays degrees of freedom for chi-squared tests.
Expects minor changes in some of the effect sizes and their confidence
intervals due to changes in {statsExpressions}.
More models supported in ggcoefstats: fixest, ivFixed, ivprobit,
riskRegression.
ggcorrmat supports partial correlations.ggcoefstats no longer supports exponentiate argument. If it is
specified, the user will have to themselves adjust the scales
appropriately.
ggcorrmat defaults have changed significantly:
As a matter of good practice, the p-values are adjusted by default for multiple comparisons.
The default matrix is upper type, and not the full matrix, which features many redundant comparisons and self-correlations diagonally.
Default text size for legend has been increased to 15 and background grid has been removed.
In the prior release, when the GitHub version of BayesFactor wasn't
present, ggwithinstats just outright failed to run for ANOVA designs. This
has been fixed.
Drops broomExtra from dependencies. All regression modeling-related
analysis now relies on easystats ecosystem.
ggpiestats and ggbarstats don't support returning dataframes. See FAQ
vignette on how to get these dataframes:
https://www.indrapatil.com/ggstatsplot/articles/web_only/faq.html#faq-1
ggpiestats and ggbarstats were not supposed to support returning Bayes
Factor for paired contingency table analysis, which is not supported in
BayesFactor itself.
ggcoefstats defaults to displaying the intercept term. Also, when the
degrees of freedom are not available for t-statistic, they are displayed
to be Inf, in keeping with easystats conventions.
Instead of showing significance of p-values with APA's asterisks
conventions, ggbarstats now instead shows the actual p-values from
one-sample proportion tests.
ggcoefstats: Glm.ggpiestats and ggbarstats no longer have the vestigial arguments main
and condition, which are superseded by x and y, respectively.For consistency and to reduce confusion, all Bayes Factor (irrespective of
whether in the subtitle or caption) are always in favor of null over
alternative (BF01).
ggscatterstats.
Although it was not the default, when turned on, it definitely created a
cluttered plot.ggbetweenstats and ggwithinstats functions now default to
pairwise.comparisons = TRUE.Plot borders are now removed from the default theme.
pairwiseComparisons re-exports are deprecated.More models supported in ggcoefstats: BFBayesFactor, betamfx, crq,
coxph.penal, geeglm, glht, glmm, lm_robust, lqm, lqmm,
manova, maov, margins, negbinmfx, logitmfx, logitsf, margins,
poissonmfx, betaor, negbinirr, logitor, metafor, metaplus,
orm, poissonirr, semLm, semLme, vgam.
ggpiestats gains label.repel argument to cover contexts in which the
labels might overlap. Setting it to TRUE will minimize such an overlap.
ggbetweenstats and ggwithinstats gain ggsignif.args argument to make
it easy to change aesthetics of the pairwise comparison geom.
The subtitle and caption for Bayes Factor tests now also provide information about posterior estimates, when relevant.
Removed unused intent_morality dataset.
ggcoefstats retires caption.summary argument. So, by default, the
caption is going to contain as much information as it can and the users can
then choose to modify the default caption using ggplot2 functions.The argument method for ggcorrmat has been renamed to matrix.method,
since it was confusing whether this method referred to correlation method.
For both ggpiestats and ggbarstats, the count labels no longer include n = in them as this was confusing since all labels had n = in them
with no further explanation about how this n differed from n in the
proportion test.
No longer relies on groupedstats package.
The pairwise.annotation argument for ggbetweenstats and ggwithinstats
is deprecated. This was done because-
Different fields have different schema for what significance levels asterisks represent.
The p-value labels also contain information about whether they are adjusted for multiple comparisons.
normality_message and bartlett_message helper functions have been
removed. This is because model assumption checks don't really fall under the
purview of this package. There are excellent visualization tools out there
for model assumption checks (ggResidpanel, performance, DHARMa,
olsrr, etc.), which should be preferred over unhelpful messages with only
p-values that these functions were printing. For what it's worth, the
functions where these messages were displayed (ggbetweenstats or
ggwithinstats) feature visualizations rich enough and defaults sensible
enough that most of the time one can either assess these assumptions from
the plots or need not worry about them.ggcoefstats has been refactored to reflect that
broomExtra::tidy_parameters now defaults to parameters package instead
of broom. It also loses the following vestigial arguments:
p.adjust.method and coefficient.type.
Reverts aligning title and subtitle with the plot and not the axes, since it
looked pretty ugly (esp., ggcoefstats) and was causing problems for
labels.
factor.levels (for ggpiestats) and labels.legend (for ggbarstats)
are deprecated. If users would like to changes the names for factor levels,
this should be done outside of {ggstatsplot}.
The non-parametric post hoc test for between-subjects design has been changed from Dwass-Steel-Crichtlow-Fligner test to Dunn test.
ggcoefstats: bayesGARCH, clm2, clmm2,
mcmc.list, robmixglm.ggcorrmat no longer returns matrices of correlation coefficients or other
details. It now returns either a plot or a data frame and this can data
frame can then be used to create matrices.
ggbarstats loses x.axis.orientation argument. This argument was supposed
to help avoid overlapping x-axis label, but now ggplot2 3.3.0 has a
better way to handle this.More models supported in ggcoefstats: bayesx, BBmm, brmultinom,
lmerModLmerTest, lrm.
Specifying output = "proptest" for ggpiestats and ggbarstats functions
will now return a data frame containing results from proportion test.
ggbetweenstats and ggwithinstats will display pairwise comparisons even
if results.subtitle is set to FALSE.
ggcorrmat supports computing Bayes Factors for Pearson's r correlation.
ggbetweenstats and ggwithinstats now support pairwise comparisons for
Bayes Factor test.
For changes related to subtitle details, see changes made in new version of
statsExpressions 4.0.0:
https://CRAN.R-project.org/package=statsExpressions/news/news.html
ggbetweenstats and ggwithinstats no longer print dataframes containing
results from pairwise comparisons tests because this is too cluttering for
the user's console. The users are now instead advised to either extract this
data frame using ggplot2::ggplot_build() function or use the
pairwiseComparisons::pairwise_comparisons() function used in the
background by {ggstatsplot} to carry out this analysis.
Due to changes in one of the downstream dependencies, {ggstatsplot} now
expects the minimum R version to be 3.6.0.
ggcorrmat now internally relies on correlation for correlation
analyses.
ggbarstats no longer displays "percent" for Y-axis label as this was
redundant information.
Continuing the argument cleanup that began in 0.3.0, ggcoefstats gains
point.args argument instead of individuals point.* arguments.
The subtitles are more explicit about the details of the test. For the same
reason stat.title argument from all relevant functions is retired since
this argument was supposed to be for entering some additional details about
the test. Additionally, the plot titles and subtitles for some of the plots
are aligned with the plot.
ggcorrmat legend, in case of missing values, shows mode - instead of
median - for the distribution of sample pairs.
The following vestigial arguments are retired:
caption.default in ggcorrmat
k.caption.summary in ggcoefstats
This is a hotfix release to correct some of the failing tests and other minor
breakages resulting from the new release of ggplot2 3.3.0.
ggpiestats loses sample.size.label argument since this information is
included in the goodness of fit test results itself. So setting
proportion.test to FALSE will suppress this information.To give users more flexibility in terms of modifying the aesthetic defaults for
all geoms included in the {ggstatsplot} plots (each plot typically has
multiple geoms), the package now uses a new form of syntax. Previously, each
geom had a separate argument to specify each aesthetic (e.g., geom_point
would get arguments like point.size, point.color, etc.), which resulted in
functions with a massive number of arguments and was unsustainable in the long
run. Instead, {ggstatsplot} functions now expect a list of such arguments for
the respective geom (e.g., geom_point will have point.args argument where a
list of arguments list(size = 5, color = "darkgreen", alpha = 0.8) can be
supplied).
All grouped_ functions have been refactored to reduce the number of
arguments. These functions now internally use the new combine_plots
instead of combine_plots. The additional arguments to primary functions
can be provided through .... These changes will not necessarily break the
existing code but will lead to some minor graphical changes (e.g., if you
were providing labels argument explicitly, it will be ignored).
All functions lose the return argument, which was supposed to be
alternative to enter output. But this was just leading to more confusion
on the user's part. The biggest user-visible impact this is going to have is
that ggcorrmat will no longer be backward-compatible. The older scripts
will still work but if the return argument was anything except "plot",
it will just be ignored.
ggcorrmat no longer has corr.method argument. To be consistent with rest
of the functions in this package, the type of statistics should be specified
using type argument. Additional, it gains a new argument
ggcorrplot.args, which can be used to pass additional arguments to the
underlying plotting function (ggcorrplot::ggcorrplot).
Both gghistostats and ggdotplotstats now use the following arguments to
modify geoms corresponding to the lines and labels:
test.value.line.args, test.value.label.args, centrality.line.args,
centrality.label.args. This helps avoid specifying millions of arguments.
Removes the vestigial ggplot_converter function.
ggpiestats and ggbarstats remove the following vestigial arguments:
facet.wrap.name, bias.correct, bar.outline.color. The bar.proptest
and facet.proptest arguments were difficult to remember and confusing and
are replaced by a common proportion.test argument. Additionally, the
following arguments have all been removed and replaced by label argument:
slice.label, bar.label, data.label. These plethora of options was a
headache to remember.
gghistostats loses the following arguments: fill.gradient, low.color,
high.color. It made no sense to add a color gradient to this plot when the
Y-axis already displayed the information about what the bar represented.
ggscatterstats loses the following arguments: palette and package.
Since this function requires only two colors, it didn't make much sense to
use color palettes to specify this. They can be instead specified using
xfill and yfill. You can always use paletteer::paletteer_d to get a
vector of color values and then provide values of your choosing to xfill
and yfill.
Removes sorting options in ggbetweenstats and ggwithinstats functions.
This is something the users can easily do before entering the data in these
functions.
ggcorrmat was never supposed to work with Kendall's correlation
coefficient but it accidentally did. This is no longer the case.
{ggstatsplot} now has a logo, thanks to Sarah! :)
The default theme_ggstatsplot changes slightly. The biggest change is that
the title and the subtitle for plots are now aligned to the left of the
plot. This change also forced the legend for ggpiestats to be displayed on
the right side of the plot rather than at the bottom.
More models supported in ggcoefstats: BBreg, bcplm, bife, cglm,
crch, DirichReg, LORgee, zcpglm, zeroinfl.
ipmisc: bartlett_message,
normality_message. A few other internal data wrangling functions now
reside in ipmisc.To have a more manageable length of function arguments, additional aesthetic
specifications for any given geom can be provided via a dedicated *.args
argument. For example, all aesthetic arguments for geom_vline can be
provided via vline.args, for geom_errorbarh via errorbar.args, etc.
{ggstatsplot} continues with its conscious uncoupling that started in
0.1.0 release: The following functions have now been moved to
{statsExpressions} package: subtitle_meta_parametric and
bf_meta_message and follow a more logical nomenclature. For the same
reason, lm_effsize_ci function is also no longer exported and lives in the
groupedstats package.The summary caption no longer displays log-likelihood value because it tends to be not available for a number of regression model objects and so the caption was unnecessarily being skipped.
New dataset included: bugs_wide
More models supported in ggcoefstats: cgam, cgamm, coxme, cpglm,
cpglmm, complmrob, feis, flexsurvreg, glmx, hurdle, iv_robust,
mixor, rqss, truncreg, vgam.
Removed vestigial arguments from ggcorrmat (e.g., exact, continuity,
etc.) and ggpiestats (bf.prior, simulate.p.value, B, etc.).
ggbetweenstats and ggwithinstats no longer produce error with variables
with pattern mean (#336).pairwise_p has been reintroduced as a number of users found it useful to
call the function from {ggstatsplot} itself rather than using
pairwiseComparisons package.ggbetweenstats and ggwithinstats use [ instead of ( to display
confidence intervals. Additionally, $$\mu$$ denoted sample mean, but was
confused with population mean by some users. So these functions instead
display $$\hat{\mu}$$.
More models supported in ggcoefstats: bmlm, coeftest
Adapts to the new syntax provided in paletteer package.
ggrepel in ggcoefstats function have been removed. The users can instead
provide all such arguments in a list to stats.labels.args argument.ggbetweenstats and ggwithinstats no longer produce incorrect label if
the data frame already contains a variable named n (#317) or variables
with pattern mean (#322).
ggbetweenstats and ggwithinstats mean labels respect k argument
(#331).MINOR
ggcoefstats now uses parameters::p_value instead of sjstats::p_value,
as requested by the maintainer of that package. This might lead to
differences in p-values for lmer models.
More models supported in ggcoefstats: blavaan, bracl, brglm2,
glmc, lavaan, nlreg, slm, wbgee.
ggcoefstats gains only.significant argument to only display display
stats labels for significant effects. This can be helpful when a large
number of regression coefficients are to be displayed in a single plot.
MINOR
magrittr, ellipsis, purrrlyr.MAJOR
ggbetweenstats and ggwithinstats pairwise comparisons were adjusted or
not for multiple comparisons.ANNOUNCEMENTS
{ggstatsplot} is undergoing conscious uncoupling whereby all the statistical
processing functions that make stats subtitles are being moved to a new package
called {statsExpressions}. This new package will act as a backend that handles
all things statistical processing. This will not affect the end users of
{ggstatsplot} unless you have been using the helper functions.
Additionally, multiple pairwise comparison tests are being moved to an
independent package called pairwiseComparisons.
This uncoupling is designed to achieve two things:
Make the code base of more manageable size in {ggstatsplot}, which will
make package development a bit easier.
Make the workflow more customizable since now you can prepare your own plots
and then use {statsExpressions} to display results in the plot rather than
relying on {ggstatsplot} default plots which are heavily opinionated and
not appealing to everyone.
All helper functions subtitle_* and bf_* have been moved to the new
{statsExpressions} package.
subtitle_ and bf_ functions,
subtitle_contingency_tab and bf_contingency_tab now use the arguments
x and y instead of main and condition.Major refactoring to reduce the codesize and to rely fully on rlang.
There was confusion about what did the red point in ggbetweenstats and
ggbetweenstats plots represents. Now the label also contains $\mu$ to
highlight that what is being displayed is a mean value.
To be consistent with the rest of the functions, ggpiestats and
ggbarstats now uses the following aliases for arguments: x for main
and y for condition. This change is backward-compatible and should not
pose any problems for scripts that used main and condition arguments in
these functions.
Most subtitle expressions now report details about the design. In case of between-subjects design, this will be $n_{obs}$, while in case of repeated measures design, this will be $n_{pairs}$.
pairwise.annotation now defaults to "p.value" rather than "asterisk"
for ggbetweenstats and ggwithinstats (and their grouped_ variants)
functions. This was done because the asterisk conventions are not consistent
across various scientific disciplines.
New dataset included: bugs_long, for repeated measures designs with NAs
present in the data.
{ggstatsplot} now uses rcompanion to compute Spearman's rho and
Kendall's W. Therefore, DescTools is removed from dependencies.
ggcoefstats supports following objects: bglmerMod, blmerMod, lme,
mclogit, mmclogit, tobit, wblm.
ggcoefstats now respects conf.int. It internally always defaulted to
conf.int = TRUE in broom::tidy irrespective of what was specified by the
user.
It was painfully confusing for a lot of users what exactly the asterisks in
each facet of ggpiestats signified. So instead now ggpiestats displays
more detailed results from a goodness of fit (gof) test. No such change is
made for ggbarstats because there is no space to include more details
above the bar.
Removed conf.method and conf.type arguments for ggcoefstats. Also,
p.kr argument removed because ggcoefstats will begin to rely on
parameters instead of sjstats package to compute p-values for some
regression models.
ggwithinstats caption, displayed by default, was
incorrect. This has been fixed. This stemmed from a line of code which
should have been paired = TRUE, but was instead paired = FALSE.ggcoefstats defaults to bf.message = TRUE to be consistent with the rest
of the functions in the package.
ggcoefstats supports the following class of objects: epi.2by2, negbin,
emmGrid, lmrob, glmrob, glmmPQL, data.table.
bf_ttest is introduced as a general function. The previously exported
bf_one_sample_ttest and bf_two_sample_ttest become its aliases.
bf_meta_message syntax changes to adapt to updates made to metaBMA
package (thanks to #259).
The vestigial arguments axis.text.x.margin.t, axis.text.x.margin.r,
axis.text.x.margin.b, axis.text.x.margin.l for ggcorrmat have been
removed. The margins can be adjusted using ggplot2::margin().
gghistostats no longer allows data argument to be NULL. This is to
make this function's syntax consistent with rest of the functions in this
package (none of which allow data to be NULL). This also removes
confusion that arose for some users when data couldn't be NULL for its
grouped_ cousin (grouped_gghistostats).
outlier_df function is no longer exported since it was always meant to be
an internal function and was accidentally exported during initial release and
was retained for a while for backward compatibility.
Instead of having two separate functions that dealt with repeated measures
(subtitle_friedman_nonparametric) and between-subjects
(subtitle_kw_nonparametric), a single function
subtitle_anova_nonparametric handles both of these designs with the
paired argument determining which test is run.
All functions that supported Bayes Factor analysis (type = "bf") will only
return BF value and the scale used. Previously, this was a mix of parametric
statistics and BF, which was confusing and often times misleading since
these two types of analyses relied on different tests.
The default for bf.message has been changed from FALSE to TRUE. This
is to make the Bayes Factor analysis more visible to the user.
ggscatterstats returns only plot (without any statistical details) when
the specified model is not linear (i.e., either when method argument is
not "lm" or when formula is not y ~ x).New functions ggwithinstats (and its grouped_ variant) are introduced as
a counterpart to ggbetweenstats to handle repeated measures designs.
For repeated measures ANOVA, subtitle_anova_nonparametric now returns
confidence intervals for Kendall's W.
All functions get return argument that can be used to return either
"plot", "subtitle", or "caption". This makes it unnecessary to
remember which subtitle function is to be used where. As a result, in the
next release, all subtitle making functions will not be exported and are
encouraged not be used either by other developers or by users.
Both subtitle_anova_robust and subtitle_anova_parametric gain a new
argument paired to support repeated measures designs.
ggcoefstats can support following new model objects: drc, mlm.
ggcoefstats gains bf.message argument to display a caption containing
results from Bayesian random-effects meta-analysis. It therefore gains a new
dependency: metaBMA.
ggpiestats and ggcatstats will now display Cramer's V as effect size
for one-sample proportion tests.
All functions gain stat.title argument (NULL by default) that can be
used to prefix the subtitle with a string of interest. This is possibly
useful for specifying the details of the statistical test.
pairwise_p() function no longer outputs conf.low and conf.high columns
when parametric post hoc tests are run. This is because these values were
accurate only when no p-value adjustment was carried out.
Instead of using the internal function cor_test_ci, ggscatterstats
instead used SpearmanRho function from DescTools package. This was done
to reduce number of custom internal functions used to compute CIs for
various effect sizes. {ggstatsplot} therefore gains DescTools as a
dependency.
The sampling.plan argument default for ggbarstats function has been
changed from "indepMulti" to "jointMulti" to be consistent with its
sister function ggpiestats.
ggcoefstats can support following new model objects: rjags.
New VR_dilemma dataset for toying around with within-subjects design.
subtitle_t_onesample supports both Cohen's d and Hedge's g as effect
sizes and also produces their confidence intervals. Additionally,
non-central variants of these effect sizes are also supported. Thus,
gghistostats and its grouped_ variant gets two new arguments:
effsize.type, effsize.noncentral.
ggpiestats used to display odds ratio as effect size for paired designs
(McNemar test). But this was only working when the analysis was a 2 x 2
contingency table. It now instead displays Cohen's G as effect size, which
generalizes to any kind of design.
The internal function outlier_df to add a column specifying outlier status
of any given data point is now exported.
{ggstatsplot} previously relied on an internal function chisq_v_ci to
compute confidence intervals for Cramer's V using bootstrapping but it was
pretty slow. It now instead relies on rcompanion package to compute
confidence intervals for V. {ggstatsplot}, therefore, gains a new
dependency.
subtitle_mann_nonparametric and subtitle_t_onesample now computes effect
size r and its confidence intervals as $$Z/\sqrt{N}$$ (with the help of
rcompanion package), instead of using Spearman correlation.
subtitle_t_onesample no longer has data as the optional argument. This
was done to be consistent with other subtitle helper functions.New function ggbarstats (and its grouped_ variant) introduced for making
bar charts (thanks to #78).
ggcoefstats also displays a caption with model summary when meta-analysis
is required.
gghistostats and its grouped_ variant has a new argument normal.curve
to superpose a normal distribution curve on top of the histogram (#138).
ggcoefstats can support following new regression model objects: brmsfit,
gam, Gam, gamlss, mcmc, mjoint, stanreg.
New function to convert plots which are not of gg/ggplot class to
ggplot class objects.
Instead of using effsize to compute Cohen's d and Hedge's g,
{ggstatsplot} now relies on a new (#159) internal function
effect_t_parametric to compute them. This removes effsize from
dependencies.
To be consistent with other functions in this package, both ggbarstats and
ggpiestats gain results.subtitle which can be set to FALSE if
statistical analysis is not required, in which case subtitle argument can
be used to provide alternative subtitle.
ggbetweenstats now defaults to using noncentral-t distribution for
computing Cohen's d and Hedge's g. To get variants with central-t
distribution, use effsize.noncentral = FALSE.All grouped_ functions had argument title.prefix that defaulted to
"Group". It now instead defaults to NULL, in which case the prefix will
variable name for grouping.var argument.
To accommodate non-parametric tests, subtitle_template function can now
work with parameter = NULL.
For ggbetweenstats, details contained in the subtitle for non-parametric
test are modified. It now uses Spearman's rho-based effect size estimates.
This removes coin from dependencies.
ggbetweenstats and its grouped_ variant gain a new argument
axes.range.restrict (which defaults to FALSE). This restricts y-axes
limits to minimum and maximum of y variable. This is what these functions
were doing by default in the past versions, which created issues for
additional ggplot components using the ggplot.component argument.
All bayes factor related subtitle and captions replace prior.width with
r_{Cauchy}.
ggcoefstats passes dots (...) to augment method from broom.
The helper function bf_extractor no longer provides option to extract
information about posterior distribution because these details were
incorrect. The posterior = TRUE details were not used anywhere in the
package so nothing about the results changes.
ggcorrmat didn't output pair names when output == "ci" was used. This is
fixed.ggcoefstats gains meta.analytic.effect that can be used to carry out
meta-analysis on regression estimates. This especially useful when a data
frame with regression estimates and standard error is available from prior
analyses. The subtitle is prepared with the new function
subtitle_meta_ggcoefstats which is also exported.
ggbetweenstats, ggscatterstats, gghistostats, and ggdotplotstats
(and their grouped_ variants) all gain a new ggplot.component argument.
This argument will primarily be helpful to change the individual plots in a
grouped_ plot.
ggcoefstats can support following new regression model objects: polr,
survreg, cch, Arima, biglm, glmmTMB, coxph, ridgelm, aareg,
plm, nlrq, ivreg, ergm, btergm, garch, gmm, lmodel2,
svyolr, confusionMatrix, multinom, nlmerMod, svyglm, MCMCglmm,
lm.beta, speedlm, fitdistr, mle2, orcutt, glmmadmb.
ggcoefstats didn't work when statistic argument was set to NULL. This
was not expected behavior. This has been fixed. Now, if statistic is not
specified, only the dot-and-whiskers will be shown without any labels.
subtitle_t_parametric was producing incorrect sample size information when
paired = TRUE and the data contained NAs. This has been fixed.ggscatterstats and its grouped_ variant accept both character and bare
expressions as input to arguments label.var and labe.expression (#110).
To be consistent with rest of the functions in the package, both Pearson's r, Spearman's rho, and robust percentage bend correlations also display information about statistic associated with these tests.
ggscatterstats, by default, showed jittered data points (because it relied
on position_jitter defaults). This could be visually inaccurate and,
therefore, ggscatterstats now displays points without any jitter. The user
can introduce jitter if they wish to using point.width.jitter and
point.height.jitter arguments. For similar reasons, for ggbetweenstats
and its grouped_ variant, point.jitter.height default has been changed
from 0.1 to 0 (no vertical jitter, i.e.).
Confidence interval for Kendall's W is now computed using
stats::kruskal.test. As a result, PMCMRplus removed from dependencies.
ggcoefstats gains a caption argument. If caption.summary is set to
TRUE, the specified caption will be added on top of the
caption.summary.ggcoefstats was showing wrong confidence intervals for merMod class
objects due to a bug in the broom.mixed package
(https://github.com/bbolker/broom.mixed/issues/30#issuecomment-428385005).
This was fixed in broom.mixed and so ggcoefstats should no longer have
any issues.
specify_decimal_p has been modified because it produced incorrect results
when k < 3 and p.value = TRUE (e.g., 0.002 was printed as < 0.001).
ggpiestats produced incorrect results if some levels of the factor had
been filtered out prior to using this function. It now drops unused levels
and produces correct results.
gghistostats wasn't filtering out NAs properly. This has been fixed.
New function ggdotplotstats for creating a dot plot/chart for labelled
numeric data.
All primary functions gain conf.level argument to control confidence level
for effect size measures.
As per APA guidelines, all results show results with two decimal places.
That is, the default value for k argument for all functions has been
changed from 3 to 2.
All helper functions for the ggbetweenstats subtitles have been renamed to
remove _ggbetween_ from their names as this was becoming confusing for the
user. Some of these functions work both with the between- and
within-subjects designs, so having _ggbetween_ in their names made users
suspect if they could use these functions for within-subjects designs.
{ggstatsplot} now depends on R 3.5.0. This is because some of its
dependencies require 3.5.0 to work (e.g., broom.mixed).
All theme_ functions are now exported (theme_pie(), theme_corrmat()).
ggbetweenstats now supports multiple pairwise comparison tests
(parametric, nonparametric, and robust variants). It gains a new dependency
ggsignif.
ggbetweenstats now supports eta-squared and omega-squared effect sizes for
anova models. This function gains a new argument partial.
Following functions are now reexported from the groupedstats package to
avoid repeating the same code in two packages: specify_decimal_p,
signif_column, lm_effsize_ci, and set_cwd. Therefore, groupedstats
is now added as a dependency.
gghistostats can now show both counts and proportions information on the
same plot when bar.measure argument is set to "mix".
ggcoefstats works with tidy dataframes.
The helper function untable has been deprecated in light of
tidyr::uncount, which does exactly what untable was doing. The author
wasn't aware of this function when untable was written.
All vignettes have been removed from CRAN to reduce the size of the
package. They are now available on the package website:
https://www.indrapatil.com/ggstatsplot/articles/.
subtitle_t_robust function can now handle dependent samples and gains
paired argument.
A number of tidyverse operators are now reexported by {ggstatsplot}:
%>%, %<>%, %$%.
ggscatterstats, ggpiestats, and their grouped_ variant support bayes
factor tests and gain new arguments relevant to this test.
Effect size and their confidence intervals now available for Kruskal-Wallis test.
Minor stylistic changes to how symbols for partial-eta-/omega-squared were being displayed in subtitles.
ggbetweenstats supports bayes factor tests for anova designs.
ggpiestats (and its grouped_ version) gain slice.label argument that
decides what information needs to be displayed as a label on the slices of
the pie chart: "percentage" (which has been the default thus far),
"counts", or "both".
ggcorrmat can work with cor.vars = NULL. In such case, all numeric
variables from the provided data frame will be used for computing the
correlation matrix.
Given the constant changes to the default behavior of functions, the
lifecycle badge has been changed from stable to maturing.
When the number of colors needed by a function exceeds the number of colors
contained in a given palette, informative message is displayed to the user
(with the new internal function palette_message()).
Several users had requested an easier way to turn off subtitles with results
from tests (which was already implemented in ggscatterstats and
gghistostats with the argument results.subtitle), so ggbetweenstats
also gains two new arguments to do this: results.subtitle and subtitle.
New dataset added: iris_long.
More tests added and the code coverage has now jumped to over 75%.
To avoid code repetition, there is a now a function that produces a generic message any time confidence intervals for effect size estimate are computed using bootstrapping.
The package now exports all functions used to create text expressions with
results. This makes it easy for people to use these results in their own
plots at any location they want (and not just in subtitle, the current
default for {ggstatsplot}).
ggcorrmat gains p.adjust.method argument which allows p-values for
correlations to be corrected for multiple comparisons.
ggscatterstats gains label.var and label.expression arguments to
attach labels to points.
gghistostats now defaults to not showing (redundant) color gradient
(fill.gradient = FALSE) and shows both "count" and "proportion" data.
It also gains a new argument bar.fill that can be used to fill bars with a
uniform color.
ggbetweenstats, ggcoefstats, ggcorrmat, ggscatterstats, and
ggpiestats now support all palettes contained in the paletteer package.
This helps avoid situations where people had large number of groups (> 12)
and there were not enough colors in any of the RColorBrewer palettes.
ggbetweenstats gains bf.message argument to display bayes factors in
favor of the null (currently works only for parametric t-test).
gghistostats function no longer has line.labeller.y argument; this
position is automatically determined now.
legend.title.margin function has been deprecated since ggplot2 3.0.0 has
improved on the margin issues from previous versions. All functions that
wrapped around this function now lose the relevant arguments
(legend.title.margin, t.margin, b.margin).
The argument ggstatsplot.theme has been changed to ggstatsplot.layer for
ggcorrmat function to be consistent across functions.
For consistency, conf.level and conf.type arguments for ggbetweenstats
have been deprecated. No other function in the package allowed changing
confidence interval or their type for effect size estimation. These
arguments were relevant only for robust tests anyway.
ggocorrmat argument type has been changed to matrix.type because for
all other functions type argument specifies the type of the test, while
for this function it specified the display of the visualization matrix. This
will make the syntax more consistent across functions.
ggscatterstats gains new arguments to specify aesthetics for geom point
(point.color, point.size, point.alpha). To be consistent with this
naming schema, the width.jitter and height.jitter arguments have been
renamed to point.width.jitter and point.height.jitter, resp.
gghistostats: To be compatible with JASP, natural logarithm of Bayes
Factors is displayed, and not base 10 logarithm.
ggscatterstats gains method and formula arguments to modify smoothing
functions.
ggcorrmat can now show robust correlation coefficients in the matrix
plot.
For gghistostats, binwidth value, if not specified, is computed with
(max-min)/sqrt(n). This is basically to get rid of the warnings ggplot2
produces. Thanks to Chuck Powell's PR (#43).
ggcoefstats gains a new argument partial and can display eta-squared and
omega-squared effect sizes for anovas, in addition to the prior partial
variants of these effect sizes.
ggpiestats gains digits.perc argument to show desired number of decimal
places in percentage labels.
grouped_ggpiestats wasn't working when only main variable was provided
with counts data. Fixed that.For the sake of consistency, theme_mprl is now called theme_ggstatsplot.
The theme_mprl function will still be around and will not be
deprecated, so feel free to use either or both of them since they are
identical.
ggcoefstats no longer has arguments effects and ran_params because
only fixed effects are shown for mixed-effects models.
ggpiestats can now handle within-subjects designs (McNemar test results
will be displayed).
ggbetweenstats was producing wrong axes labels when sample.size.label
was set to TRUE and user had reordered factor levels before using this
function. The new version fixes this.
ggcoefstats wasn't producing partial omega-squared for aovlist objects.
Fixed that with new version of sjstats.Removed the trailing comma from the robust correlation analyses.
gghistostats has a new argument to remove color fill gradient.
ggbetweenstats takes new argument mean.ci to show confidence intervals
for the mean values.
For lmer models, p-values are now computed using sjstats::p_value.
This removes lmerTest package from dependencies.
sjstats no longer suggests apaTables package to compute confidence
intervals for partial eta- and omega-squared. Therefore, apaTables and
MBESS are removed from dependencies.
ggscatterstats supports densigram with the development version of
ggExtra. It additionally gains few extra arguments to change aesthetics of
marginals (alpha, size, etc.).
New function: ggcoefstats for displaying model coefficients.
All functions now have ggtheme argument that can be used to change the
default theme, which has now been changed from theme_grey() to
theme_bw().
The robust correlation is no longer MASS::rlm, but percentage bend
correlation, as implemented in WRS2::pbcor. This was done to be consistent
across different functions. ggcorrmat also uses percentage bend
correlation as the robust correlation measure. This also means that
{ggstatsplot} no longer imports MASS and sfsmisc.
The data argument is no longer NULL for all functions, except
gghistostats. In other words, the user must provide a data frame from
which variables or formulas should be selected.
All subtitles containing results now also show sample size information
(n). To adjust for the inflated length of the subtitle, the default
subtitle text size has been changed from 12 to 11.
Switched back to Shapiro-Wilk test of normality to remove nortest from
imports.
ggbetweenstats and ggpiestats now display sample sizes for each level of
the groping factor by default. This behavior can be turned off by setting
sample.size.label to FALSE.
Three new datasets added: Titanic_full, movies_wide, movies_long.
Added confidence interval for effect size for robust ANOVA.
The 95% CI for Cramer'V computed using boot::boot. Therefore, the package
no longer imports DescTools.
To be consistent across correlations covered, all correlations now show estimates for correlation coefficients, confidence intervals for the estimate, and p-values. Therefore, t-values and regression coefficients are no longer displayed for Pearson's r.
The legend.title.margin arguments for gghistostats and ggcorrmat now
default to FALSE, since ggplot2 3.0.0 has better legend title margins.
ggpiestats now sorts the summary dataframes not by percentages but by the
levels of main variable. This was done to have the same legends across
different levels of a grouping variable in grouped_ggpiestats.
To remove cluttered display of results in the subtitle, ggpiestats no
longer shows titles for the tests run (these were "Proportion test" and
"Chi-Square test"). From the pie charts, it should be obvious to the user or
reader what test was run.
gghistostats also allows running robust version of one-sample test now
(One-sample percentile bootstrap).
The ggbetweenstats function can now show notched box plots. Two new
arguments notch and notchwidth control its behavior. The defaults are
still standard box plots.
Removed warnings that were appearing when outlier.label argument was of
character type.
The default color palette used for all plots is colorblind friendly.
gghistostats supports proportion and density as a value measure for
bar heights to show proportions and density. New argument bar.measure
controls this behavior.
grouped_ variants of functions ggcorrmat, ggscatterstats,
ggbetweenstats, and ggpiestats introduced to create multiple plots for
different levels of a grouping variable.
To be internally consistent, all functions in {ggstatsplot} use the
spelling color, rather than colour in some functions, while color in
others.
Removed the redundant argument binwidth.adjust from gghistostats
function. This argument was relevant for the first avatar of this function,
but is no longer playing any role.
To be internally consistent, the argument lab_col and lab_size in
ggcorrmat have been changed to lab.col and lab.size, respectively.
Added a new argument to ggstatsplot.theme function to control if
ggstatsplot::theme_mprl is to be overlaid on top of the selected ggtheme
(ggplot2 theme, i.e.).
Two new arguments added to gghistostats to allow user to change colorbar
gradient. Defaults are colorblind friendly.
Both gghistostats and ggcorrmat have a new argument
legend.title.margin to control margin adjustment between the title and the
colorbar.
The vertical lines denoting test values and centrality parameters can be
tagged with text labels with a new argument line.labeller in
gghistostats function.
centrality.para argument for ggscatterstats was not working
properly. Choosing "median" didn't show median, but the mean. This is
fixed now.Bayesian test added to gghistostats and two new arguments to also display
a vertical line for test.value argument.
Vignette added for gghistostats.
Added new function grouped_gghistostats to facilitate applying
gghistostats for multiple levels of a grouping factor.
ggbetweenstats has a new argument outlier.coef to adjust threshold used
to detect outliers. Removed bug from the same function when outlier.label
argument is of factor/character type.
Functions signif_column and grouped_proptest are now deprecated. They
were exported in the first release by mistake.
Function gghistostats no longer displays both density and count since the
density information was redundant. The density.plot argument has also been
deprecated.
ggscatterstats argument intercept has now been changed to
centrality.para. This was due to possible confusion about interpretation
of these lines; they show central tendency measures and not intercept for
the linear model. Thus the change.
The default for effsize.type = "biased" effect size for ggbetweenstats
in case of ANOVA is partial omega-squared, and not omega-squared.
Additionally, both partial eta- and omega-squared are not computed using
bootstrapping with (default) 100 bootstrap samples.
More examples added to the README document.
95% confidence intervals for Spearman's rho are now computed using broom
package. RVAideMemoire package is thus removed from dependencies.
95% confidence intervals for partial eta- and omega-squared for
ggbetweenstats function are now computed using sjstats package, which
allows bootstrapping. apaTables and userfriendlyscience packages are
thus removed from dependencies.