Hotfix release to fix a critical issue with [pingouin.pairwise_ttests()](https://pingouin-stats.org/generated/pingouin.pairwise_ttests.html#pingouin.pairwise_ttests) (see below). We strongly recommend that you update to the newest version of Pingouin and double-check your previous results if you’ve ever used the pairwise T-tests with more than one factor (e.g. mixed, factorial or 2-way repeated measures design).
**Bugfixes**
- MAJOR: Fixed a bug in [pingouin.pairwise_ttests()](https://pingouin-stats.org/generated/pingouin.pairwise_ttests.html#pingouin.pairwise_ttests) when using mixed or two-way repeated measures design. Specifically, the T-tests were performed without averaging over repeated measurements first (i.e. without calculating the marginal means). Note that for mixed design, this only impacts the between-subject T-test(s). Practically speaking, this led to higher degrees of freedom (because they were conflated with the number of repeated measurements) and ultimately incorrect T and p-values because the assumption of independence was violated. Pingouin now averages over repeated measurements in mixed and two-way repeated measures design, which is the same behavior as [JASP](https://jasp-stats.org/) or [JAMOVI](https://www.jamovi.org/). As a consequence, and when the data has only two groups, the between-subject p-value of the pairwise T-test should be (almost) equal to the p-value of the same factor in the [pingouin.mixed_anova()](https://pingouin-stats.org/generated/pingouin.mixed_anova.html#pingouin.mixed_anova) function. The old behavior of Pingouin can still be obtained using the ``marginal=False`` argument.
- Minor: Added a check in [pingouin.mixed_anova()](https://pingouin-stats.org/generated/pingouin.mixed_anova.html#pingouin.mixed_anova) to ensure that the ``subject`` variable has a unique set of values for each between-subject group defined in the ``between`` variable. For instance, the subject IDs for group1 are [1, 2, 3, 4, 5] and for group2 [6, 7, 8, 9, 10]. The function will throw an error if there are one or more overlapping subject IDs between groups (e.g. the subject IDs for group1 AND group2 are both [1, 2, 3, 4, 5]).
- Minor: Fixed a bug which caused the [pingouin.plot_rm_corr()](https://pingouin-stats.org/generated/pingouin.plot_rm_corr.html#pingouin.plot_rm_corr) and [pingouin.ancova()](https://pingouin-stats.org/generated/pingouin.ancova.html#pingouin.ancova) (with >1 covariates) to throw an error if any of the input variables started with a number (because of statsmodels / [Patsy formula formatting](https://patsy.readthedocs.io/en/latest/builtins-reference.html)).
**Enhancements**
- Upon loading, Pingouin will now use the [outdated](https://github.com/alexmojaki/outdated) package to check and warn the user if a newer stable version is available.
- Globally removed the ``export_filename`` parameter, which allowed to export the output table to a .csv file. This helps simplify the API and testing. As an alternative, one can simply use [pandas.to_csv()](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_csv.html) to export the output dataframe generated by Pingouin.
- Added the ``correction`` argument to [pingouin.pairwise_ttests()](https://pingouin-stats.org/generated/pingouin.pairwise_ttests.html#pingouin.pairwise_ttests) to enable or disable Welch’s correction for independent T-tests.