Returns the (partial) eta-squared, (partial) omega-squared statistic
or Cohen's F for all terms in an anovas. anova_stats()
returns
a tidy summary, including all these statistics and power for each term.
eta_sq(model, partial = FALSE, ci.lvl = NULL, n = 1000) omega_sq(model, partial = FALSE, ci.lvl = NULL, n = 1000) cohens_f(model) anova_stats(model, digits = 3)
model | A fitted anova-model of class |
---|---|
partial | Logical, if |
ci.lvl | Scalar between 0 and 1. If not |
n | Number of bootstraps to be generated. |
digits | Number of decimal points in the returned data frame. |
A data frame with the term name(s) and effect size statistics; if
ci.lvl
is not NULL
, a data frame including lower and
upper confidence intervals is returned. For anova_stats()
, a tidy
data frame with all statistics is returned (excluding confidence intervals).
For eta_sq()
(with partial = FALSE
), due to
non-symmetry, confidence intervals are based on bootstrap-methods. In this
case, n
indicates the number of bootstrap samples to be drawn to
compute the confidence intervals. Confidence intervals for partial
omega-squared is also based on bootstrapping.
Levine TR, Hullett CR (2002): Eta Squared, Partial Eta Squared, and Misreporting of Effect Size in Communication Research (pdf)
Tippey K, Longnecker MT (2016): An Ad Hoc Method for Computing Pseudo-Effect Size for Mixed Model. (pdf)
# load sample data data(efc) # fit linear model fit <- aov( c12hour ~ as.factor(e42dep) + as.factor(c172code) + c160age, data = efc ) eta_sq(fit)#> term etasq #> 1 e42dep 0.266 #> 2 c172code 0.005 #> 3 c160age 0.048omega_sq(fit)#> term omegasq #> 1 e42dep 0.263 #> 2 c172code 0.004 #> 3 c160age 0.048eta_sq(fit, partial = TRUE)#> term partial.etasq #> 1 e42dep 0.281 #> 2 c172code 0.008 #> 3 c160age 0.066eta_sq(fit, partial = TRUE, ci.lvl = .8)#> term partial.etasq conf.low conf.high #> 1 e42dep 0.281 0.247 0.310 #> 2 c172code 0.008 0.001 0.016 #> 3 c160age 0.066 0.047 0.089#> term power sumsq meansq df statistic p.value etasq #> 1 e42dep 1.000 426461.571 142153.857 3 80.299 0.000 0.212 #> 2 c172code 0.429 7352.049 3676.025 2 2.076 0.126 0.004 #> 3 c160age 1.000 105169.595 105169.595 1 59.408 0.000 0.052 #> 4 Residuals NA 1476436.343 1770.307 834 NA NA NA #> partial.etasq omegasq partial.omegasq cohens.f #> 1 0.224 0.209 0.221 0.537 #> 2 0.005 0.002 0.003 0.071 #> 3 0.066 0.051 0.065 0.267 #> 4 NA NA NA NA