Description

Interpret coefficient of determination (R2)

Usage

Arguments

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