Package: pmcalibration
Type: Package
Title: Calibration Curves for Clinical Prediction Models
Version: 0.1.0
Authors@R: person(given = "Stephen", family = "Rhodes", email= "steverho89@gmail.com", role=c("aut", "cre", "cph"))
Maintainer: Stephen Rhodes <steverho89@gmail.com>
Description: Fit calibrations curves for clinical prediction models and calculate several associated 
  metrics (Eavg, E50, E90, Emax). Ideally predicted probabilities from a prediction model 
  should align with observed probabilities. Calibration curves relate predicted probabilities 
  (or a transformation thereof) to observed outcomes via a flexible non-linear smoothing function. 
  'pmcalibration' allows users to choose between several smoothers (regression splines, generalized 
  additive models/GAMs, lowess, loess). Both binary and time-to-event outcomes are supported. 
  See Van Calster et al. (2016) <doi:10.1016/j.jclinepi.2015.12.005>; 
  Austin and Steyerberg (2019) <doi:10.1002/sim.8281>; 
  Austin et al. (2020) <doi:10.1002/sim.8570>.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.2.3
URL: https://github.com/stephenrho/pmcalibration
BugReports: https://github.com/stephenrho/pmcalibration/issues
Imports: Hmisc, MASS, checkmate, chk, mgcv, splines, graphics, stats,
        methods, survival, pbapply, parallel
Suggests: knitr, rmarkdown, data.table, ggplot2, rms, simsurv
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2023-09-06 00:19:48 UTC; stephenrhodes
Author: Stephen Rhodes [aut, cre, cph]
Repository: CRAN
Date/Publication: 2023-09-06 17:50:02 UTC
Built: R 4.2.0; ; 2023-09-07 12:33:52 UTC; unix
