Interpret ANOVA Effect Sizes

Source: R/interpret_omega_squared.R

Interpret ANOVA Effect Sizes

interpret_omega_squared(es, rules = "field2013", ...)

interpret_eta_squared(es, rules = "field2013", ...)

interpret_epsilon_squared(es, rules = "field2013", ...)

interpret_r2_semipartial(es, rules = "field2013", ...)

Arguments

es

Value or vector of (partial) eta / omega / epsilon squared or semipartial r squared values.

rules

Can be "field2013" (default), "cohen1992" or custom set of rules().

...

Not used for now.

Rules

  • Field (2013) ("field2013"; default)

    • ES < 0.01 - Very small

    • 0.01 <= ES < 0.06 - Small

    • 0.06 <= ES < 0.14 - Medium

    • **ES >= 0.14 ** - Large

  • Cohen (1992) ("cohen1992") applicable to one-way anova, or to partial eta / omega / epsilon squared in multi-way anova.

    • ES < 0.02 - Very small

    • 0.02 <= ES < 0.13 - Small

    • 0.13 <= ES < 0.26 - Medium

    • ES >= 0.26 - Large

References

  • Field, A (2013) Discovering statistics using IBM SPSS Statistics. Fourth Edition. Sage:London.

  • Cohen, J. (1992). A power primer. Psychological bulletin, 112(1), 155.

See also

https://imaging.mrc-cbu.cam.ac.uk/statswiki/FAQ/effectSize/

Examples

interpret_eta_squared(.02)
#> [1] "small"
#> (Rules: field2013)
interpret_eta_squared(c(.5, .02), rules = "cohen1992")
#> [1] "large" "small"
#> (Rules: cohen1992)