Last chance! 50% off unlimited learning
Sale ends in
Calculate common language effect size.
CLES(x, y)numeric, data
numeric, data
“For continuous data, it [the common language statistic] is the probability that a score sampled at random from one distribution will be greater than a score sampled from some other distribution.” (McGraw and Wong, 1992)
This function calculates the fraction of all possible pairings between x and y where the difference (y - x) is positive.
McGraw, Kenneth O. and Wong, S. P. (1992) A common language effect size statistic. Psychological Bulletin 11, 361--365. 10.1037/0033-2909.111.2.361
National Center for Health Statistics (1987) Anthropometric Reference Data and Prevalence of Overweight: United States, 1976-1980. Data from the National Health Survey, Series 11, No. 238. DHHS Publication (PHS) No. 87-1688. U.S. Government Printing Office, Washington, DC. http://www.cdc.gov/nchs/data/series/sr_11/sr11_238.pdf
# NOT RUN {
# generate synthetic data for heights in inches of 18-24
# year-old males and females (NCHS, 1987, Tables 13 and 14)
height_male <- rnorm(988, 69.7, 2.8)
height_female <- rnorm(1066, 64.3, 2.6)
# the CLES is approximately 0.92 (McGraw and Wong, 1992)
CLES(height_female, height_male)
# }
Run the code above in your browser using DataLab