interpret_r2 function

Interpret Coefficient of Determination ($R^2$)

interpret_r2(r2, rules = "cohen1988")

Arguments

• r2: Value or vector of $R^2$ values.
• rules: Can be "cohen1988" (default), "falk1992", "chin1998", "hair2011", or custom set of rules()].

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

Examples

interpret_r2(.02)
interpret_r2(c(.5, .02))

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.