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pairwiseComparisons 3.2.0

  • Due to a bug in previous versions of WRS2::lincon, even if p-value correction was method = "none", it still applied Hochberg's correction and the {pairwiseComparisons} package once again applied Holm's correction, which means the p-values were over-corrected for multiple comparisons. This bug has been fixed in WRS2 1.1-3 and therefore the users should expect slightly different p-values for between-subjects post hoc robust tests.

  • {pairwiseComparisons} now relies on {statsExpressions} for statistical analysis.

  • All included datasets have now been removed since the same datasets are also present in {statsExpressions} package.

  • No longer depends on ipmisc package.

pairwiseComparisons 3.1.6

  • Maintenance and internal changes.

  • Improvements to docs.

pairwiseComparisons 3.1.5

  • To avoid confusion among users, the trimming level for all functions is now changed from tr = 0.1 to tr = 0.2 (which is what WRS2 defaults to).

  • The ... are now passed to other methods. This can be used to specify additional arguments, like alternative (#28).

  • Gets rid of iris_long dataset, which was not used in the package.

pairwiseComparisons 3.1.3

  • Minor internal refactoring.

  • Removes insight from dependencies.

pairwiseComparisons 3.1.2

  • Minor internal refactoring.

pairwiseComparisons 3.1.1

  • Minor internal refactoring.

  • Removes the unnecessary (and confusing) significance column from all outputs.

pairwiseComparisons 3.1.0

  • To be consistent with the rest of the ggstatsverse, the Bayes Factor results are now always shown in favor of null over alternative (BF01).

  • pairwise_comparisons function gets subject.id argument relevant for repeated measures design.

pairwiseComparisons 3.0.0

  • The label column returned in pairwise_comparisons now displays the p-value adjustment method in the label itself.

  • pairwise_caption function has changed its output to reflect changes made to the p-value labels.

  • Major internal refactoring to get rid of the following dependencies: broomExtra, dunn.test, forcats, and tidyr. This comes at the cost of omission of few of the details that were previously included in the output (e.g., mean.difference column for Student's t-test).

pairwiseComparisons 2.0.1

  • Hotfix release to fix failing tests due to release of tidyBF 0.3.0.

pairwiseComparisons 2.0.0

  • Fixes a bug which affected results for within-subjects design when the dataframe wasn't sorted by x (#19).

  • This fix also now makes the results more consistent, such that irrespective of which type of statistics is chosen the group1 and group2 columns are in identical order.

pairwiseComparisons 1.1.2

  • Hot fix release to address failing tests on the old release of R (3.6).

pairwiseComparisons 1.1.1

  • For repeated measures datasets with NAs present, the Bayes Factor values were incorrect. This is fixed.

  • Internal refactoring to improve data wrangling using ipmisc.

pairwiseComparisons 1.0.0

  • Removes dependence on jmv and instead relies on dunn.test and PMCMRplus. This significantly reduces number of dependencies.

  • The non-parametric Dwass test has been changed to Dunn test.

pairwiseComparisons 0.3.1

  • Adapts to breaking changes in upcoming release of broom 0.7.0.

  • Thanks to Sarah, the package has a hexsticker. :)

pairwiseComparisons 0.3.0

  • Due to changes made to downstream dependencies, the minimum R version expected is bumped to 3.6.0.

  • Adds support for the Bayes Factor tests.

  • Exports the internal helper function pairwise_caption.

pairwiseComparisons 0.2.5

  • Maintenance release to import functions from ipmisc.

pairwiseComparisons 0.2.0

  • pairwise_comparisons_caption is removed since it was helpful only for ggstatsplot's internal graphics display and wasn't of much utility outside of that context.

pairwiseComparisons 0.1.3

  • Instead of cluttering the terminal with messages, pairwise_comparisons function now instead adds two columns (test.details and p.value.adjustment) to all outputs specifying which test was carried out and which adjustment method is being used for p-value correction.

  • Gets rid of groupedstats and crayon from dependencies.

pairwiseComparisons 0.1.2

  • With jmv 1.0.8, the results from the Dwass-Steel-Crichtlow-Fligner test will be slightly different.

pairwiseComparisons 0.1.1

  • The p.value.label in the output dataframe has been renamed to label to consider the possibility that Bayes Factor tests might also be supported in future.

  • The label now specified whether the p-value was adjusted or not for multiple comparisons.

pairwiseComparisons 0.1.0

  • First release of the package.