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Confidence interval for eta-squared

Source: R/statpsych1.R
ci.etasqr.Rd

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.

For more details, see Section 3.7 of Bonett (2021, Volume 1)

Usage

ci.etasqr(alpha, etasqr, df1, df2)

Arguments

alpha

alpha value for 1-alpha confidence

etasqr

estimated eta-squared

df1

degrees of freedom for effect

df2

error degrees of freedom

Value

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

References

Bonett DG (2021). Statistical Methods for Psychologists https://dgbonett.sites.ucsc.edu/.

Examples

ci.etasqr(.05, .15, 2, 57)
#>  Eta-squared adj Eta-squared      SE     LL     UL
#>         0.15          0.1202 0.07414 0.0102 0.3008

# Should return:
# Eta-squared  adj Eta-squared       SE      LL      UL
#        0.15           0.1202  0.07414  0.0102  0.3008