etasqr.gen.2way: Generalized eta-squared estimates in a two-factor design

In statpsych: Statistical Methods for Psychologists

Generalized eta-squared estimates in a two-factor design

Description

Computes generalized eta-square estimates in a two-factor design where one or both factors are classification factors. If both factors are treatment factors, then partial eta-square estimates are typically recommended. The eta-squared estimates from this function can be used in the etasqr.adj function to obtain bias adjusted estimates.

For more details, see Section 3.12 of Bonett (2021, Volume 1)

Usage

etasqr.gen.2way(SSa, SSb, SSab, SSe)

Arguments

SSa	sum of squares for factor A
SSb	sum of squares for factor B
SSab	sum of squares for A x B interaction
SSe	error (within) sum of squares

Value

Returns a 3-row matrix. The columns are:

• A - estimate of eta-squared for factor A

• B - estimate of eta-squared for factor B

• AB - estimate of eta-squared for A x B interaction

References

\insertRef

Bonett2021statpsych

Examples

etasqr.gen.2way(12.3, 15.6, 5.2, 7.9)

# Should return:
#                                           A         B        AB
# A treatment, B classification:      0.300000 0.5435540 0.1811847
# A classification, B treatment:      0.484252 0.3804878 0.2047244
# A classification, B classification: 0.300000 0.3804878 0.1268293
 

statpsych documentation built on Jan. 13, 2026, 1:07 a.m.