Interpret standardized differences
Interpretation of standardized differences using different sets of rules of thumb.
interpret_d(d, rules = "cohen1988", ...) interpret_g(g, rules = "cohen1988") interpret_delta(delta, rules = "cohen1988")
d, g, delta |
Value or vector of effect size values. |
rules |
Can be |
... |
Not directly used. |
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 the d_to_r() conversion, see interpret_r())
d < 0.2 - Very small
0.2 <= d < 0.41 - Small
0.41 <= d < 0.63 - Moderate
d >= 0.63 - Large
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.
interpret_d(.02) interpret_d(c(.5, .02)) interpret_d(.3, rules = "lovakov2021")
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.