Cohen's Effect Size

Computes the Cohen's d and Hedges'g effect size statistics.

CohenD(x, y = NULL, pooled = TRUE, correct = FALSE, conf.level = NA, na.rm = FALSE)

Arguments

x

a (non-empty) numeric vector of data values.

y

a (non-empty) numeric vector of data values.

pooled

logical, indicating whether compute pooled standard deviation or the whole sample standard deviation. Default is TRUE.

correct

logical, indicating whether to apply the Hedges correction. (Default: FALSE)

conf.level

confidence level of the interval. Set this to NA, if no confidence intervals should be calculated. (This is the default)

na.rm

logical. Should missing values be removed? Defaults to FALSE.

Value

a numeric vector with 3 elements:

d

the effect size d

lwr.ci

lower bound of the confidence interval

upr.ci

upper bound of the confidence interval

References

Cohen, J. (1988) Statistical power analysis for the behavioral sciences (2nd ed.) Academic Press, New York.

Hedges, L. V. & Olkin, I. (1985) Statistical methods for meta-analysis Academic Press, Orlando, FL

Smithson, M.J. (2003) Confidence Intervals, Quantitative Applications in the Social Sciences Series, No. 140. Thousand Oaks, CA: Sage. pp. 39-41

Author

Andri Signorell <andri@signorell.net>, William Revelle <revelle@northwestern.edu> (CI)

See also

mean, var

Examples

x <- d.pizza$price[d.pizza$driver=="Carter"]
y <- d.pizza$price[d.pizza$driver=="Miller"]

CohenD(x, y, conf.level=0.95, na.rm=TRUE)
#>            d       lwr.ci       upr.ci 
#> -0.212277884 -0.430317413  0.006061792 
#> attr(,"magnitude")
#> [1] "small"