logistic_cal: Run logistic calibration

In pmcalibration: Calibration Curves for Clinical Prediction Models

Run logistic calibration

Description

Assess 'weak' calibration (see, e.g., Van Calster et al. 2019) via calibration intercept and calibration slope.

Usage

logistic_cal(y, p)

Arguments

y	binary outcome
p	predicted probabilities (these will be logit transformed)

Value

an object of class logistic_cal containing glm results for calculating calibration intercept and calibration slope

References

Van Calster, B., McLernon, D. J., Van Smeden, M., Wynants, L., & Steyerberg, E. W. (2019). Calibration: the Achilles heel of predictive analytics. BMC medicine, 17(1), 1-7.

Examples

library(pmcalibration)
# simulate some data
n <- 500
dat <- sim_dat(N = n, a1 = .5, a3 = .2)

# predictions
p <- with(dat, invlogit(.5 + x1 + x2 + x1*x2*.1))

logistic_cal(y = dat$y, p = p)

pmcalibration documentation built on Sept. 8, 2023, 5:10 p.m.