eelbrain.table.stats

eelbrain.table.stats(y, row, col=None, match=None, sub=None, fmt='%.4g', funcs=('mean',), ds=None, title=None, caption=None, format=True)

Make a table with statistics

Parameters

• y (Var) – Dependent variable.

• row (Union[Factor, Interaction, NestedEffect, str]) – Model specifying rows

• col (Union[Factor, Interaction, NestedEffect, str, None]) – Model specifying columns.

• match (Union[Factor, Interaction, NestedEffect, str, None]) – Identifier for repeated measures data; aggregate within subject before computing statistics.

• sub (Union[Var, ndarray, str, None]) – Only use part of the data.

• fmt (str) – How to format values.

• funcs (Sequence[Union[str, Callable]]) – A list of statistics functions to show (all functions must take an array argument and return a scalar; strings are interpreted as numpy functions).

• ds (Optional[Dataset]) – If a Dataset is provided, y, row, and col can be strings specifying members.

• title (Union[str, List[str], FMTextElement, FMTextConstant, None]) – Table title.

• caption (Union[str, List[str], FMTextElement, FMTextConstant, None]) – Table caption.

• format (bool) – Return a formatted table (instead of a Dataset)

Returns

Table with statistics.

Return type

table

Examples

>>> ds = datasets.get_uts()
>>> table.stats('Y', 'A', 'B', ds=ds)
            B
     -----------------
     b0        b1
----------------------
a0   0.1668    -0.3646
a1   -0.4897   0.8746

>>> table.stats('Y', 'A', ds=ds, funcs=['mean', 'std'])
Condition   Mean     Std
--------------------------
a0          0.6691   1.37
a1          0.8596   1.192