Computes a confidence interval for a population eta-squared, partial eta-squared, or generalized eta-squared in a fixed-factor between-subjects design. An approximate bias adjusted estimate is computed, and an approximate standard error is recovered from the confidence interval.
ci.etasqr(alpha, etasqr, df1, df2)alpha value for 1-alpha confidence
estimated eta-squared
degrees of freedom for effect
error degrees of freedom
Returns a 1-row matrix. The columns are:
Eta-squared - eta-squared (from input)
adj Eta-squared - bias adjusted eta-squared estimate
SE - recovered standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
ci.etasqr(.05, .241, 3, 116)
#> Eta-squared adj Eta-squared SE LL UL
#> 0.241 0.2213707 0.06258283 0.1040229 0.3493431
# Should return:
# Eta-squared adj Eta-squared SE LL UL
# 0.241 0.2213707 0.06258283 0.1040229 0.3493431