Interpret Coefficient of Determination (\(R^2\))
Arguments
- r2
Value or vector of \(R^2\) values.
- rules
Can be
"cohen1988"
(default),"falk1992"
,"chin1998"
,"hair2011"
, or custom set ofrules()
].
Rules
For Linear Regression
Cohen (1988) (
"cohen1988"
; default)R2 < 0.02 - Very weak
0.02 <= R2 < 0.13 - Weak
0.13 <= R2 < 0.26 - Moderate
R2 >= 0.26 - Substantial
Falk & Miller (1992) (
"falk1992"
)R2 < 0.1 - Negligible
R2 >= 0.1 - Adequate
For PLS / SEM R-Squared of latent variables
Chin, W. W. (1998) (
"chin1998"
)R2 < 0.19 - Very weak
0.19 <= R2 < 0.33 - Weak
0.33 <= R2 < 0.67 - Moderate
R2 >= 0.67 - Substantial
Hair et al. (2011) (
"hair2011"
)R2 < 0.25 - Very weak
0.25 <= R2 < 0.50 - Weak
0.50 <= R2 < 0.75 - Moderate
R2 >= 0.75 - Substantial
References
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd Ed.). New York: Routledge.
Falk, R. F., & Miller, N. B. (1992). A primer for soft modeling. University of Akron Press.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
Examples
interpret_r2(.02)
#> [1] "weak"
#> (Rules: cohen1988)
#>
interpret_r2(c(.5, .02))
#> [1] "substantial" "weak"
#> (Rules: cohen1988)
#>