eelbrain.test.pairwise¶
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eelbrain.test.
pairwise
(y:Union[eelbrain._data_obj.Var, str], x:Union[eelbrain._data_obj.Factor, eelbrain._data_obj.Interaction, eelbrain._data_obj.NestedEffect, str], match:Union[eelbrain._data_obj.Factor, eelbrain._data_obj.Interaction, eelbrain._data_obj.NestedEffect, str]=None, sub:Union[eelbrain._data_obj.Var, numpy.ndarray, str]=None, ds:eelbrain._data_obj.Dataset=None, par:bool=True, corr:Union[NoneType, str]='Hochberg', trend:Union[bool, str]=True, title:str='{desc}', mirror:bool=False)¶ Pairwise comparison table
Parameters: - y : Var
Dependent measure.
- x : categorial
Categories to compare.
- match : None | Factor
Repeated measures factor.
- sub : None | index-array
Perform tests with a subset of the data.
- ds : Dataset
If a Dataset is given, all data-objects can be specified as names of Dataset variables.
- par : bool
Use parametric test for pairwise comparisons (use non-parametric tests if False).
- corr : None | ‘hochberg’ | ‘bonferroni’ | ‘holm’
Method for multiple comparison correction.
- trend : None | str
Marker for a trend in pairwise comparisons.
- title : str
Title for the table.
- mirror : bool
Redundant table including all row/column combinations.
Returns: - table : FMText Table
Table with results.