# Convert between Odds ratios and Risk ratios

Source:`R/convert_between_OR_to_RR.R`

`oddsratio_to_riskratio.Rd`

Convert between Odds ratios and Risk ratios

## Arguments

- OR, RR
Risk ratio of

`p1/p0`

or Odds ratio of`odds(p1)/odds(p0)`

, possibly log-ed.`OR`

can also be a logistic regression model.- p0
Baseline risk

- log
Take in or output the log of the ratio (such as in logistic models).

- ...
Arguments passed to and from other methods.

## Value

Converted index, or if `OR`

is a logistic regression model, a
parameter table with the converted indices.

## References

Grant, R. L. (2014). Converting an odds ratio to a range of plausible relative risks for better communication of research findings. Bmj, 348, f7450.

## See also

Other convert between effect sizes:
`d_to_cles()`

,
`d_to_r()`

,
`eta2_to_f2()`

,
`odds_to_probs()`

## Examples

```
p0 <- 0.4
p1 <- 0.7
(OR <- probs_to_odds(p1) / probs_to_odds(p0))
#> [1] 3.5
(RR <- p1 / p0)
#> [1] 1.75
riskratio_to_oddsratio(RR, p0 = p0)
#> [1] 3.5
oddsratio_to_riskratio(OR, p0 = p0)
#> [1] 1.75
m <- glm(am ~ factor(cyl), data = mtcars,
family = binomial())
oddsratio_to_riskratio(m)
#> Warning: 'p0' not provided.RR is relative to the intercept (p0 = 0.73) - make sure your intercept is meaningful.
#> Warning: CIs are back-transformed from the logit scale.
#> Parameter | Risk Ratio | 95% CI
#> ---------------------------------------
#> (Intercept) | 0.73 |
#> cyl [6] | 0.59 | [0.11, 1.16]
#> cyl [8] | 0.20 | [0.02, 0.70]
#>
#> Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
#> computed using a Wald z-distribution approximation.
```