pingouin.compute_effsize_from_t

pingouin.compute_effsize_from_t(tval, nx=None, ny=None, N=None, eftype='cohen')

Compute effect size from a T-value.

Parameters:

tvalfloat

T-value

nx, nyint, optional

Group sample sizes.

Nint, optional

Total sample size (will not be used if nx and ny are specified)

eftypestring, optional

Desired output effect size.

Returns:

effloat

Effect size

See also

compute_effsize

Calculate effect size between two set of observations.

convert_effsize

Conversion between effect sizes.

Notes

If both nx and ny are specified, the formula to convert from t to d is:

\[d = t * \sqrt{\frac{1}{n_x} + \frac{1}{n_y}}\]

If only N (total sample size) is specified, the formula is:

\[d = \frac{2t}{\sqrt{N}}\]

Examples

1. Compute effect size from a T-value when both sample sizes are known.

>>> from pingouin import compute_effsize_from_t
>>> tval, nx, ny = 2.90, 35, 25
>>> d = compute_effsize_from_t(tval, nx=nx, ny=ny, eftype='cohen')
>>> print(d)
0.7593982580212534

2. Compute effect size when only total sample size is known (nx+ny)

>>> tval, N = 2.90, 60
>>> d = compute_effsize_from_t(tval, N=N, eftype='cohen')
>>> print(d)
0.7487767802667672