rstatix (version 0.1.1)

cohens_d: Compute Cohen's d Measure of Effect Size

Description

Compute the effect size for t-test. T-test conventional effect sizes, poposed by Cohen, are: 0.2 (small efect), 0.5 (moderate effect) and 0.8 (large effect).

Usage

cohens_d(data, formula, paired = FALSE, mu = 0, var.equal = FALSE)

Arguments

data

a data.frame containing the variables in the formula.

formula

a formula of the form x ~ group where x is a numeric variable giving the data values and group is a factor with one or multiple levels giving the corresponding groups. For example, formula = TP53 ~ cancer_group.

paired

a logical indicating whether you want a paired test.

mu

theoretical mean, use for one-sample t-test. Default is O.

var.equal

a logical variable indicating whether to treat the two variances as being equal. If TRUE then the pooled variance is used to estimate the variance otherwise the Welch (or Satterthwaite) approximation to the degrees of freedom is used.

Value

a data frame containing the Cohen's d and the magnitude.

Examples

# NOT RUN {
# One-sample t test effect size
ToothGrowth %>% cohens_d(len ~ 1, mu = 0)

# Two indepedent samples t-test effect size
ToothGrowth %>% cohens_d(len ~ supp, var.equal = TRUE)

# Paired samples effect size
df <- data.frame(
  id = 1:5,
  pre  = c(110, 122, 101, 120, 140),
  post = c(150, 160, 110, 140, 155)
)
df <- df %>% gather(key = "treatment", value = "value", -id)
head(df)

df %>% cohens_d(value ~ treatment, paired = TRUE)
# }