predieval
0.1.1Assessing Performance of Prediction Models for Predicting Patient-Level Treatment Benefit
Overview
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.
Install
Health
- NOTE r-devel-linux-x86_64-debian-clang
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-06-0911 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0811 OK · 1 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Downloads
Repository
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Repository practices
4 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/esm-ispm-unibe-ch/predieval on 2026-07-19.
Dependencies
Nothing depends on this yet.
Code & Tests
Datasets
People & History
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2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 0.1.1Latest
- unarchivedReturned to CRAN2022-04-19
- archivedRemoved from CRAN2022-04-09required archived package 'Matching'
- 0.1.02022-03-28
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2022-03-28
- Total releases
- 2 / 4 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 4.1
- Bundled data
- 102 KB / 2 files
- Download size
- 115 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet