d.to.cles: Conversion from Cohen's d to Common Language Effect Size

Description

Helper function to convert Cohen's d to common language effect size (or vice versa). The result is the probability of superiority for independent samples. It can be interpreted as the probability that a randomly selected observation from Group 1 exceeds a randomly selected observation from Group 2. The rationale is the same for paired-samples and one-sample designs, but the interpretation differs: For paired samples, it can be interpreted as the probability that the difference score (i.e., the score under Condition 1 minus the score under Condition 2) is greater than zero for a randomly selected individual. For a one-sample design, it can be interpreted as the probability that a randomly selected observation is greater than the reference value (e.g., 0).

Usage

d.to.cles(d, design = c("independent", "paired", "one.sample"), verbose = 1)
cles.to.d(cles, design = c("independent", "paired", "one.sample"), verbose = 1)

Value

d: Cohen's d
cles: common language effect size.

Arguments

d: Cohen's d
design: character; one of the "independent", "paired", or "one.sample". The default is "independent".
verbose: 1 by default (returns test, hypotheses, and results), if 2 a more detailed output is given (plus key parameters and definitions), if 0 no output is printed on the console.
cles: common language effect size.

Examples

Run this code

d.to.cles(0.20) # small
d.to.cles(0.50) # medium
d.to.cles(0.80) # large

cles.to.d(0.5562315)
cles.to.d(0.6381632)
cles.to.d(0.7141962)

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