interpret_cohens_d {effectsize} | R Documentation |
Interpret Standardized Differences
Description
Interpretation of standardized differences using different sets of rules of thumb.
Usage
interpret_cohens_d(d, rules = "cohen1988", ...)
interpret_hedges_g(g, rules = "cohen1988")
interpret_glass_delta(delta, rules = "cohen1988")
Arguments
d , g , delta |
Value or vector of effect size values. |
rules |
Can be |
... |
Not directly used. |
Rules
Rules apply to equally to positive and negative d (i.e., they are given as absolute values).
Cohen (1988) (
"cohen1988"
; default)-
d < 0.2 - Very small
-
0.2 <= d < 0.5 - Small
-
0.5 <= d < 0.8 - Medium
-
d >= 0.8 - Large
-
Sawilowsky (2009) (
"sawilowsky2009"
)-
d < 0.1 - Tiny
-
0.1 <= d < 0.2 - Very small
-
0.2 <= d < 0.5 - Small
-
0.5 <= d < 0.8 - Medium
-
0.8 <= d < 1.2 - Large
-
1.2 <= d < 2 - Very large
-
d >= 2 - Huge
-
Lovakov & Agadullina (2021) (
"lovakov2021"
)-
d < 0.15 - Very small
-
0.15 <= d < 0.36 - Small
-
0.36 <= d < 0.65 - Medium
-
d >= 0.65 - Large
-
Gignac & Szodorai (2016) (
"gignac2016"
, based on thed_to_r()
conversion, seeinterpret_r()
)-
d < 0.2 - Very small
-
0.2 <= d < 0.41 - Small
-
0.41 <= d < 0.63 - Moderate
-
d >= 0.63 - Large
-
References
Lovakov, A., & Agadullina, E. R. (2021). Empirically Derived Guidelines for Effect Size Interpretation in Social Psychology. European Journal of Social Psychology.
Gignac, G. E., & Szodorai, E. T. (2016). Effect size guidelines for individual differences researchers. Personality and individual differences, 102, 74-78.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd Ed.). New York: Routledge.
Sawilowsky, S. S. (2009). New effect size rules of thumb.
Examples
interpret_cohens_d(.02)
interpret_cohens_d(c(.5, .02))
interpret_cohens_d(.3, rules = "lovakov2021")