scikit_posthocs.posthoc_dunnett

scikit_posthocs.posthoc_dunnett(a: list | ndarray | DataFrame, val_col: str = None, group_col: str = None, control: str = None, alternative: Literal['two-sided', 'less', 'greater'] = 'two-sided', sort: bool = False, to_matrix: bool = True) → Series | DataFrame

Dunnett’s test [1, 2, 3] for multiple comparisons against a control group, used after parametric ANOVA. The control group is specified by the control parameter.

Parameters:

  • a (array_like or pandas DataFrame object) – An array, any object exposing the array interface or a pandas DataFrame. Array must be two-dimensional.

  • val_col (str, optional) – Name of a DataFrame column that contains dependent variable values (test or response variable). Values should have a non-nominal scale. Must be specified if a is a pandas DataFrame object.

  • group_col (str, optional) – Name of a DataFrame column that contains independent variable values (grouping or predictor variable). Values should have a nominal scale (categorical). Must be specified if a is a pandas DataFrame object.

  • control (str, optional) – Name of the control group within the group_col column. Values should have a nominal scale (categorical). Must be specified if a is a pandas DataFrame.

  • alternative (['two-sided', 'less', or 'greater'], optional) – Whether to get the p-value for the one-sided hypothesis (‘less’ or ‘greater’) or for the two-sided hypothesis (‘two-sided’). Defaults to ‘two-sided’.

  • sort (bool, optional) – Specifies whether to sort DataFrame by group_col or not. Recommended unless you sort your data manually.

  • to_matrix (bool, optional) – Specifies whether to return a DataFrame or a Series. If True, a DataFrame is returned with some NaN values since it’s not pairwise comparison. Default is True.

Returns:

result – P values.

Return type:

pandas.Series or pandas.DataFrame

References