Generalized eta-squared estimates in a two-factor design

Source: R/statpsych1.R

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.

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

Examples

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

# 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