Source code for statsmodels.stats.multicomp

"""

Created on Fri Mar 30 18:27:25 2012
Author: Josef Perktold
"""

from statsmodels.sandbox.stats.multicomp import (  # noqa:F401
    tukeyhsd, MultiComparison)

__all__ = ['tukeyhsd', 'MultiComparison']


[docs] def pairwise_tukeyhsd(endog, groups, alpha=0.05, use_var='equal'): """ Calculate all pairwise comparisons with TukeyHSD or Games-Howell. Parameters ---------- endog : ndarray, float, 1d response variable groups : ndarray, 1d array with groups, can be string or integers alpha : float significance level for the test use_var : {"unequal", "equal"} If ``use_var`` is "equal", then the Tukey-hsd pvalues are returned. Tukey-hsd assumes that (within) variances are the same across groups. If ``use_var`` is "unequal", then the Games-Howell pvalues are returned. This uses Welch's t-test for unequal variances with Satterthwaite's corrected degrees of freedom for each pairwise comparison. Returns ------- results : TukeyHSDResults instance A results class containing relevant data and some post-hoc calculations, including adjusted p-value Notes ----- This is just a wrapper around tukeyhsd method of MultiComparison. Tukey-hsd is not robust to heteroscedasticity, i.e. variance differ across groups, especially if group sizes also vary. In those cases, the actual size (rejection rate under the Null hypothesis) might be far from the nominal size of the test. The Games-Howell method uses pairwise t-tests that are robust to differences in variances and approximately maintains size unless samples are very small. .. versionadded:: 0.15 ` The `use_var` keyword and option for Games-Howell test. See Also -------- MultiComparison tukeyhsd statsmodels.sandbox.stats.multicomp.TukeyHSDResults """ return MultiComparison(endog, groups).tukeyhsd(alpha=alpha, use_var=use_var)

Last update: Feb 19, 2025