eelbrain.test.MannWhitneyU¶

class
eelbrain.test.
MannWhitneyU
(y, x, c1=None, c0=None, match=None, sub=None, ds=None, tail=0, continuity=True)¶ MannWhitney Utest (nonparametric independent measures test)
The test data can be specified in two forms:
In long form, with
y
supplying the data,x
specifying condition for each case.With
y
andx
supplying data for the two conditions.
 Parameters
y (Var) – Dependent variable. Alternatively, the first of two variables that are compared.
x (categorial) – Model containing the cells which should be compared. Alternatively, the second of two varaibles that are compared.
c1 (str  tuple  None) – Test condition (cell of
x
).c1
andc0
can be omitted ifx
only contains two cells, in which case cells will be used in alphabetical order.c0 (str  tuple  None) – Control condition (cell of
x
).match (categorial) – Units within which measurements are related (e.g. ‘subject’ in a withinsubject comparison). If match is unspecified, it is assumed that
y
andx
are two measurements with matched cases.sub (indexarray) – Perform the test with a subset of the data.
ds (Dataset) – If a Dataset is specified, all dataobjects can be specified as names of Dataset variables.
tail (0  1  1) – Which tail of the tdistribution to consider: 0: both (twotailed, default); 1: upper tail (onetailed); 1: lower tail (onetailed).
continuity (bool) – Continuity correction (default
True
).
 Variables
See also
TTestRelated
parametric alternative
Notes
Based on
scipy.stats.mannwhitneyu()
.