interpret_oddsratio: Interpret Odds Ratio

In effectsize: Indices of Effect Size

Interpret Odds Ratio

Description

Interpret Odds Ratio

Usage

interpret_oddsratio(OR, rules = "cohen1988", p0 = NULL, log = FALSE, ...)

Arguments

OR	Value or vector of (log) odds ratio values.
rules	If "cohen1988" (default), OR is transformed to a standardized difference (via oddsratio_to_d()) and interpreted according to Cohen's rules (see interpret_cohens_d(); see Chen et al., 2010). If a custom set of rules() is used, OR is interpreted as is.
p0	Baseline risk. If not specified, the d to OR conversion uses am approximation (see details).
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).

• 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))

effectsize documentation built on April 4, 2025, 1:48 a.m.