NEWS
tidystats 0.7
Changes
- Removed the
rlang, checkmate, stringr, readr, purrr, tibble, dplyr, and tidyr dependencies.
- Added a
by argument to describe_data() and count_data() for grouping data by one or more variables.
Documentation
- Added a Microsoft Word add-in article and a privacy statement article to the pkgdown website.
- Renamed the "Reusing statistics" vignette to "Converting statistics to a data frame".
Internal changes
- Added internal string helper functions (
remove_string, detect_string, extract_string) to replace stringr functionality.
- Added internal data frame helper functions (
dots_to_names, group_names, stack_rows) to replace dplyr, tidyr, and purrr functionality.
- Rewrote all tests to use direct value comparisons instead of golden JSON files, removing the dependency on stored reference data.
tidystats 0.6.3 (2025-04-06)
Changes
- Updated to maintain support with the lme4 package, which renamed the deviance statistic to -2*log(L).
- Updated the README.
tidystats 0.6.2 (2024-07-14)
Changes
- Updated the package to maintain support for all currently supported statistical functions.
tidystats 0.6.1 (2024-04-09)
New
- Added CITATION file. Use
citation("tidystats") to see how to cite tidystats.
Changes
- Updated the package to maintain support for all currently supported statistical functions.
tidystats 0.6
Breaking changes
- Redesigned the tidystats structure to be more expandable. This breaks compatibility with the Microsoft Word add-in. An update for the Microsoft Word add-in is in the works and will be released soon.
Changes
- Renamed the
results argument in add_stats() to list
- Removed the multiplication by 100 in
count_data()'s pct column to make it
easier to present the numbers as percentages (e.g., using
scales::label_percent()). You can still obtain percentages using the new
pct argument.
- Removed the
pct column from the output of describe_data().
- Improved names in
anova() tests.
New
- Added two new arguments to
add_stats(): args and class. The args argument can be used to supply additional arguments to customize which statistics are extracted from a particular analysis. For a list of supported functions, see the "Details" section in the help document of add_stats(). The class argument can be used to explicitly indicate the class of the analysis you want to add. Sometimes the output of a particular analysis returns an object with insufficient information for tidystats to know how to extract the statistics. By using the class argument, you can tell tidystats what kind of object it is so that it can nevertheless extract the statistics. For a list of supported classes, see the Details section of the help document of add_stats().
- Added support for the
confint() function from the stats package using the new class argument in `add_stats().
- Added support for the
alpha(), corr.test(), mardia(), and ICC() functions from the psych package.
- Added support for the
icc() function from the irr package.
- Added support for the
cohen.d() function from the effsize package.
- Added support for the
emmeans() function from the emmeans package.
- Added support for the
test() function on the result of contrast() on the result of emmeans() from the emmeans package.
- Added support for
lme(), nlme(), gls(), and anova() from the nlme package.
- Added support for many more functions from the stats package.
- Added support for the effectsize package.
- Added support for the effsize package.
- Added support for the afex package.
- Added a
pct argument to count_data() to return proportions instead of percentages.
tidystats 0.5.2 (2023-04-14)
- A minor bug fix update to keep the package on CRAN.
Miscellaneous
- Removed info message that is displayed when the package is loaded.
tidystats 0.5.1 (2022-01-04)
Changes
- Renamed the
variable column in the output of describe_data() to var.
- Improved ordering of the columns in the output of
describe_data().
- Removed automatically setting the method to 'Generic test' when adding a custom test. This means you can set the method yourself now.
- Renames the
variable column to var in describe_data().
describe_data() now (again) has support for multiple variables. You can provide more than 1 column name (separated by commas) to calculate descriptives for each variable.
Bug fixes
- Using
tidy_stats() on ungrouped count data produced with count_data() is now properly tidied.
- Fixed order of columns in
describe_data() when the data is grouped.
- Fixed a bug when trying to add the results of a multilevel model ("Error in summary$ngrps[[names(summary$ngrps) == group$name]] :
attempt to select more than one element in vectorIndex")
- Fixed GitHub issue #8.
tidystats 0.5 (2020-09-21)
Breaking changes
- Changed the way certain model results are parsed. The estimate is now parsed as a list containing the name of the estimate and the value of the estimate. Models are now parsed to extract the following types of lists: statistics, terms, pairs, groups, and effects. This new parsing unites t-tests, ANOVA, and regression, including multilevel regression.
New
- Added support for generic tests. If tidystats does not support a particular analysis, you can create your own generic test by providing a list of statistics.
- Improved support for
anova().
- Added support for more BayesFactor functions.
- Added a pkgdown website for the package.
- Added several vignettes, including an introduction to tidystats, how to use the
tidy_stats_to_data_frame() function, and a description of the tidystats taxonomy.
Miscellaneous
tidystats 0.4.1 (2020-06-15)
Changes
read_stats() now converts Inf character strings to numeric.write_stats() now has a digits argument that determines the number of decimals for saved numbers (default: 6).
New
- Added support for
anova().
- Added
count_data() again.
Bug fixes
- Fixed a bug in
describe_data() caused by the dplyr 1.0.0 update.
Miscellaneous
- Added tests to minimize bugs
- Added two vignettes
tidystats 0.4 (2019-09-12)
Breaking changes
- tidystats has been completely redesigned in terms of how statistics are combined together. While previously the output of statistical models was converted to a tidy data frame, the output is now converted to a list, with an entirely different structure. The reason for this change is that lists are more machine-readable, enabling more interesting features down the line. It is still possible to convert the list of statistics to a single data frame with a new function called
tidy_stats_to_data_frame().
- The significant changes made to tidystats has resulted in the loss of some previously supported statistical functions. For a list of currently supported statistical functions, see the help document of
add_stats() or the README.
- All
report() functions have been removed for now. These may return (if I get the impression these are liked) but for now I am focusing my development time on creating a Word add-in that will enable researchers to use a tidystats-produced file for reporting statistics in Microsoft Word.
describe_data() no longer accepts multiple column names. The goal of the function is now to calculate the descriptives of a single column (which can still be grouped to calculate the descriptives for each group level).count_data() has been removed.
Changes
add_stats() now has a type argument to specify whether an analysis was a primary analysis, secondary analysis, or exploratory analysis.add_stats() now has a preregistered argument to specify whether an analysis was preregistered or not.
New
- Added an example dataset called 'quote_source' containing data of a replication of Lorge & Curtiss (1936) that was part of the Many Labs project (Klein et al., 2014)
tidystats 0.3 (2019-01-03)
Changes
- Changed the argument order in the family of
add_stats() functions. Previously, the model output or tidy data frame was the first argument. This allowed you to directly pipe the model output into add_stats() (using magrittr's %>%). However, an alternative approach is to have the tidystats list to be the first argument. This allows you create a long sequence of pipes. You start with the results list, add a model via add_stats(), pipe the result into the next add_stats(), and so on. Since you often store your model output in variable names anyway, this is probably more convenient. Additionally, this probably also keeps your script more tidy (you can do this at the end of your data analysis script).
- Certain statistical models are now tidied differently due to the addition of a 'group' column. Several models like multilevel models, meta-analytic models, and arguably also regression models have more than just terms (e.g., model fit), so to distinguish between coefficients and other parts of the output, a 'group' column has been added. This also means usage of the
report() is affected, as now the group should be specified when necessary. Affected models are regression, within-subjects ANOVA, multilevel models, and meta-analysis models.
- Removed the
identifier column from each list element when using read_stats().
- Reordered the columns of
tidy_stats.lm() and tidy_stats.glm() to be consistent with the other tidy_stats() functions.
- Added check for an existing identifier in
add_stats_to_model().
- Added warnings in case unsupported output is added (e.g., a pre-tided data frame).
read_stats() now removes empty columns from each list element.
New
- Added a new function called
inspect(). This function accepts a tidystats results list or the output of a statistical model and will display all results in RStudio's Viewer pane. This allows the user to visually inspect the results and, importantly, copy results in APA style to their clipboard. This function is aimed at users who prefer not to use R Markdown or when you want to quickly run a model and get the results in APA-style. This new function works well with Microsoft Word, but does not work with Apple Pages (some of the styling is lost when copying the results).
- Added a
class argument to add_stats() and add_stats_to_model(). Some statistical tests return a normal data.frame or matrix, which does not specify which test produced the results. This makes it difficult for tidystats to figure out how to tidy the result. Previously, we solved this by add_stats() accepting pre-tidied data frames. Now we added a the class argument to specify the name of the function that produced the results, so that we can then tidy it for you. Run ?add_stats to see a list of supported classes and see the help document of tidy_stats.confint() for an example.
- Under the hood: Added a generic report function for single values called
report_statistic(). Consequently, all report functions have been updated to use this new generic function.
- Added support for
glm().
- Added support for lme4's
lmer() and lmerTest's lmer().
- Added support for psych's
alpha().
- Added support for psych's
ICC().
- Added support for stats'
confint() via the new class argument in add_stats() and add_stats_to_model().
Bug fixes
- Fixed a bug that would incorrectly classify ANOVAs as One-way ANOVAs when character variables were used rather than factors.
- Prepared for dplyr 0.8.
Miscellaneous
- Added tests to the R package to minimize bugs.
- Made the code and documentation more consistent.
- Added an under-the-hood helper function to rename statistics columns.
tidystats 0.2 (2018-05-06)
Changes
- Renamed
describe() to describe_data() so that it no longer conflicts with psych's describe().
- Changed
describe_data() to no longer accept non-numeric variables, but added the feature that descriptives can be calculated for more than 1 variable at a time. It is recommended to use the count_data() function for non-numeric variables.
- Renamed
tidy_descriptives() to tidy_describe_data() and improved the function. A notable change is that var information is now returned to identify which descriptives belong to which variable. Also changed the group delimiter to ' - '.
write_stats() now prettifies the numbers using prettyNum() when saving them to disk.
New
- Improved
report() function. The method now supports the option to retrieve a single statistic from any tidy stats data frame. This will allow you to report all statistics, even when reporting functions for a specific method are not yet supported.
- Added quick report functions for means and standard deviations. Instead of using
report() you can use M() and SD() to quickly report the mean or standard deviation, without having to specify that particular statistic. Less typing!
- Added an option called 'tidystats_list' in
options() to set a default list. By setting the tidystats list in options(), you do not need to specify the list in the results argument of report(). Less typing!
- Reporting regression results will now include a check for whether confidence intervals are included, and report them.
- Added skewness and kurtosis to
describe_data()
- Added new
count_data() function to calculate count descriptives of categorical data. Also added a tidy_count_data() function to tidy the output of this new function.
- Added support for
chisq.test() and wilcox.test().
- Added a better default
identifier to add_stats(). If you supply a variable to be added to the tidystats list, and no identifier is provided, it will take the variable name as the identifier. If you pipe the results into add_stats() then the old default identifier will be used (e.g., "M1").
- Added identifier check to
report(). The function will now throw an error when the identifier does not exist.
- Added statistic check to all report functions. The function will now throw an error when the statistic does not exist.
- Improved
report_p_value() to support multiple p-values.
- Updated documentation to be more consistent and to take into account the changes made in the current update.
Bug fixes
- Fixed bug that it was assumed that confidence intervals in
htest objects were always 95% confidence intervals.
- Fixed bug in report functions that would occur when no statistic argument was provided.
- Removed spaces from terms in
aov() output.
- Removed a leading space from the method information of a Two Sample t-test.
- Improved
add_stats_to_model(). The method previously required a term and did not automatically complete information (e.g., method information).
tidystats 0.1 (2017-10-29)