interpret_oddsratio {effectsize}

Interpret Odds Ratio

Description

Interpret Odds Ratio

Usage

interpret_oddsratio(OR, rules = "chen2010", log = FALSE, ...)

Arguments

OR

Value or vector of (log) odds ratio values.

rules

Can be "⁠chen2010"⁠ (default), "cohen1988" (through transformation to standardized difference, see oddsratio_to_d()) or custom set of rules().

log

Are the provided values log odds ratio.

...

Currently not used.

Rules

Rules apply to OR as ratios, so OR of 10 is as extreme as a OR of 0.1 (1/10).

• Chen et al. (2010) ("chen2010"; default)

  • OR < 1.68 - Very small

  • 1.68 <= OR < 3.47 - Small

  • 3.47 <= OR < 6.71 - Medium

  • **OR >= 6.71 ** - Large

• Cohen (1988) ("cohen1988", based on the oddsratio_to_d() conversion, see interpret_cohens_d())

  • OR < 1.44 - Very small

  • 1.44 <= OR < 2.48 - Small

  • 2.48 <= OR < 4.27 - Medium

  • **OR >= 4.27 ** - Large

References

• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd Ed.). New York: Routledge.

• Chen, H., Cohen, P., & Chen, S. (2010). How big is a big odds ratio? Interpreting the magnitudes of odds ratios in epidemiological studies. Communications in Statistics-Simulation and Computation, 39(4), 860-864.

• Sánchez-Meca, J., Marín-Martínez, F., & Chacón-Moscoso, S. (2003). Effect-size indices for dichotomized outcomes in meta-analysis. Psychological methods, 8(4), 448.

Examples

interpret_oddsratio(1)
interpret_oddsratio(c(5, 2))