`scipy.stats._mstats_extras:compare_medians_ms`

Signature

def compare_medians_ms(group_1, group_2, axis = None)

Compares the medians from two independent groups along the given axis.

The comparison is performed using the McKean-Schrader estimate of the standard error of the medians.

group_1 : array_like: First dataset. Has to be of size >=7.
group_2 : array_like: Second dataset. Has to be of size >=7.
axis : int, optional: Axis along which the medians are estimated. If None, the arrays are flattened. If axis is not None, then group_1 and group_2 should have the same shape.

compare_medians_ms : {float, ndarray}: If axis is None, then returns a float, otherwise returns a 1-D ndarray of floats with a length equal to the length of group_1 along axis.

from scipy import stats
a = [1, 2, 3, 4, 5, 6, 7]
b = [8, 9, 10, 11, 12, 13, 14]

✓

stats.mstats.compare_medians_ms(a, b, axis=None)

✗

np.float64(1.0693225866553746e-05)

The function is vectorized to compute along a given axis.

import numpy as np
rng = np.random.default_rng()
x = rng.random(size=(3, 7))
y = rng.random(size=(3, 8))

✓

stats.mstats.compare_medians_ms(x, y, axis=1)

✗

array([0.31771, 0.24629, 0.27995])