Interpret Odds Ratio
Arguments
- OR
Value or vector of (log) odds ratio values.
- rules
If
"cohen1988"
(default),OR
is transformed to a standardized difference (viaoddsratio_to_d()
) and interpreted according to Cohen's rules (seeinterpret_cohens_d()
; see Chen et al., 2010). If a custom set ofrules()
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 theoddsratio_to_d()
conversion, seeinterpret_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)
#> [1] "very small"
#> (Rules: cohen1988)
#>
interpret_oddsratio(c(5, 2))
#> [1] "large" "small"
#> (Rules: cohen1988)
#>