eelbrain.test.TTestRelated
- class eelbrain.test.TTestRelated(y, x, c1=None, c0=None, match=None, sub=None, data=None, tail=0)
Related-measures t-test
The test data can be specified in two forms:
In long form, with
y
supplying the data,x
specifying condition for each case andmatch
determining which cases are related.In wide/repeated measures form, with
y
andx
both supplying data with matching case order.
- 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.match (categorial) – Units within which measurements are related (e.g. ‘subject’ in a within-subject comparison). If match is unspecified, it is assumed that
y
andx
are two measurements with matched cases.sub (index-array) – Perform the test with a subset of the data.
data (Dataset) – If a Dataset is specified, all data-objects can be specified as names of Dataset variables.
tail (0 | 1 | -1) – Which tail of the t-distribution to consider: 0: both (two-tailed, default); 1: upper tail (one-tailed); -1: lower tail (one-tailed).
- Variables:
t (float) – T-value.
p (float) – P-value.
tail (0 | 1 | -1) – Tailedness of the p value.
difference (Var) – Difference values.
df (int) – Degrees of freedom.
c1_mean (float) – Mean of condition
c1
.c0_mean (float) – Mean of condition
c0
.d (float) – Cohen’s d.
full (FMText) – Full description of the test result.
See also
WilcoxonSignedRank
non-parametric alternative