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Effect size

Source: R/effect_size.R
Cohen_d_s.Rd

Calculate Cohen's d and Hedges' g introduced in Lakens (2013).

Usage

Cohen_d_s(
  y1,
  y2,
  alternative = "two.sided",
  alpha = 0.05,
  mu = 0,
  return_CI = FALSE
)

Hedges_g_s(
  y1,
  y2,
  alternative = "two.sided",
  alpha = 0.05,
  mu = 0,
  return_CI = FALSE
)

Arguments

y1

A numeric vector.

y2

A numeric vector.

alternative

Character (default: "two.sided"). Specifies the alternative hypothesis. Available options are c("two.sided", "less", "greater").

alpha

Numeric (default: 0.05). Significance level (0 - 1) for hypothesis testing.

mu

Numeric (default: 0).

return_CI

Logical (default: FALSE). Whether to return the confidence interval of the effect size.

Value

A numeric scalar or a numeric vector of length 3, depends on return_CI.

Details

Refer to Lakens (2013), the Cohen's d is the formula 1, the Hedges' g is the formula 4. Their confidence interval (CI) were calculated based on formula 2, by transforming the d and g back to t to fit the general confidence interval calculation. For detailed and precise CI estimates, please use the effectsize package.

References

Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4. https://doi.org/10.3389/fpsyg.2013.00863