Convert Between Metrics of Change in Probabilities and Probabilities

Convert Between Metrics of Change in Probabilities and Probabilities

Usage

oddsratio_to_probs(OR, p0, log = FALSE, odds = FALSE, ...)

logoddsratio_to_probs(logOR, p0, log = TRUE, odds = FALSE, ...)

riskratio_to_probs(RR, p0, odds = FALSE, ...)

arr_to_probs(ARR, p0, odds = FALSE, ...)

nnt_to_probs(NNT, p0, odds = FALSE, ...)

Arguments

OR, logOR, RR, ARR, NNT

Odds-ratio of odds(p1)/odds(p0), log-Odds-ratio of log(odds(p1)/odds(p0)), Risk ratio of p1/p0, Absolute Risk Reduction of p1 - p0, or Number-needed-to-treat of 1/(p1 - p0). OR and logOR can also be a logistic regression model.

p0

Baseline risk

log

If:

• TRUE:

  • In oddsratio_to_*(), OR input is treated as log(OR).

  • In *_to_oddsratio(), returned value is log(OR).

• FALSE:

  • In logoddsratio_to_*(), logOR input is treated as OR.

  • In *_to_logoddsratio(), returned value is OR.

odds

Should odds be returned instead of probabilities?

...

Arguments passed to and from other methods.

Value

Probabilities (or probability odds).

See also

oddsratio(), riskratio(), arr(), and nnt(), odds_to_probs(), and oddsratio_to_arr() and others.

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
(ARR <- p1 - p0)
#> [1] 0.3
(NNT <- arr_to_nnt(ARR))
#> [1] 3.333333

riskratio_to_probs(RR, p0 = p0)
#> [1] 0.7
oddsratio_to_probs(OR, p0 = p0)
#> [1] 0.7

all.equal(nnt_to_probs(NNT, p0 = p0, odds = TRUE),
          probs_to_odds(p1))
#> [1] TRUE

arr_to_probs(-ARR, p0 = p1)
#> [1] 0.4
nnt_to_probs(-NNT, p0 = p1)
#> [1] 0.4



# RR |>
#   riskratio_to_arr(p0) |>
#   arr_to_oddsratio(p0) |>
#   oddsratio_to_nnt(p0) |>
#   nnt_to_probs(p0)