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://indrajeetpatil.github.io/statsExpressions/news/index.html
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_comparions() function implementation now lives in {statsExpressions} package, although it will continue to be exported from {ggstatsplot} package.
The details about pairwise test for 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 the same reason, the effect size for one-way contingency table has changed from Cramer’s V to Pearson’s C.
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.
Minimum needed R version is now 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.
All functions are more robust in the sense that when statistical analysis fails, they will return only the plots with no subtitles/captions. This helps avoid difficult-to-diagnose edge case failures when the primary functions are used in 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.
To avoid confusion among users, the default trimming level for all functions is now changed from 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.
Setting mean.path = FALSE in ggwithinstats produced incorrect colors for points (#470). This bug was introduced in 0.6.5 and is now fixed.
If user had set options(scipen = 999) in their session, the p-value formatting for ggpiestats and ggcoefstats looked super-ugly (#478). 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://indrajeetpatil.github.io/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).
Retires centrality parameter tagging functionality of 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.
Small p-values (< 0.001) are now displayed in scientific notation.
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.
The 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: https://www.tidyverse.org/blog/2020/03/ggplot2-3-3-0/#rewrite-of-axis-code
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.
Following functions are now re-exported from 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.
Supports robust and Bayes Factors for random-effects meta-analysis.
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.
To be consistent with all the other 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 accidently 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 exressions 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://indrajeetpatil.github.io/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.