Package: predieval
Type: Package
Title: Assessing Performance of Prediction Models for Predicting
        Patient-Level Treatment Benefit
Version: 0.1.0
Author: Orestis Efthimiou
Maintainer: Orestis Efthimiou <oremiou@gmail.com>
Description: Methods for assessing the performance of a prediction model with respect to identifying patient-level treatment benefit. All methods are applicable for continuous and binary outcomes, and for any type of statistical or machine-learning prediction model as long as it uses baseline covariates to predict outcomes under treatment and control. 
License: GPL (>= 2)
Depends: R (>= 4.1)
Imports: stats, Hmisc (>= 4.6-0), ggplot2 (>= 3.3.5), MASS (>= 7.3),
        Matching (>= 4.9-11)
Encoding: UTF-8
URL: https://github.com/esm-ispm-unibe-ch/predieval
LazyData: true
RoxygenNote: 7.1.2
NeedsCompilation: no
Packaged: 2022-03-26 13:45:10 UTC; Orestis
Repository: CRAN
Date/Publication: 2022-03-28 08:10:02 UTC
