ggstatsplot 0.0.7.9000 Unreleased

NEW FEATURES

  • ggcoefstats gains meta.analysis.subtitle that can be used to carry out meta-analysis on regression estimates. This especially useful when a dataframe 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.

MINOR CHANGES

  • Confidence interval for Kendall’s W is now computed using stats::kruskal.test. As a result, PMCMRplus removed from dependencies.

ggstatsplot 0.0.7 2018-12-08

BUG FIXES

  • 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.

MAJOR CHANGES

  • 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. TThis 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 depcreated 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: %>%, %<>%, %$%.

MINOR CHANGES

  • 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 dataframe 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 repitition, there is a now a function that produces a generic message any time confidence intervals for effect size estimate are computed using bootstrapping.

ggstatsplot 0.0.6 2018-09-30

MAJOR CHANGES

  • 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.

BREAKING CHANGES

  • legend.title.margin function has been depcrecated 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 virsualization 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.

MINOR CHANGES

  • 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 perc.k argument to show desired number of decimal places in percentage labels.

BUG FIXES

  • grouped_ggpiestats wasn’t working when only main variable was provided with counts data. Fixed that.

ggstatsplot 0.0.5 2018-08-14

MAJOR CHANGES

  • 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).

BUG FIXES

  • 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.

MINOR CHANGES

  • 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.).

ggstatsplot 0.0.4 2018-07-05

MAJOR CHANGES

  • 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 dataframe 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.

MINOR CHANGES

  • Switched back to Shapiro-Wilk test of normality to remove nortest from imports.
  • ggpiestats can now handle dataframes with
  • 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).

ggstatsplot 0.0.3 2018-05-22

NEW FEATURES

  • 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.

MAJOR CHANGES

  • 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 fucntion, 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.

MINOR CHANGES

  • 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.

BUG FIXES

  • The centrality.para argument for ggscatterstats was not working properly. Choosing "median" didn’t show median, but the mean. This is fixed now.

ggstatsplot 0.0.2 2018-04-28

NEW FEATURES

  • 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.

MAJOR CHANGES

  • 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 interpreation 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.

MINOR CHANGES

  • 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.

ggstatsplot 0.0.1 2018-04-03

  • First release of the package.