The Wally Calibration Plot for Risk Prediction Models
Overview
A prediction model is calibrated if, roughly, for any percentage x we can expect that x subjects out of 100 experience the event among all subjects that have a predicted risk of x%. A calibration plot provides a simple, yet useful, way of assessing the calibration assumption. The Wally plot consists of a sequence of usual calibration plots. Among the plots contained within the sequence, one is the actual calibration plot which has been obtained from the data and the others are obtained from similar simulated data under the calibration assumption. It provides the investigator with a direct visual understanding of the shape and sampling variability that are common under the calibration assumption. The original calibration plot from the data is included randomly among the simulated calibration plots, similarly to a police lineup. If the original calibration plot is not easily identified then the calibration assumption is not contradicted by the data. The method handles the common situations in which the data contain censored observations and occurrences of competing events.
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Paul F. Blanche <paulfblanche@gmail.com>’
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Authors@R: c(person(given = c("Paul", "F"),
family = "Blanche",
role = "aut",
email = "paulfblanche@gmail.com"),
person(given = c("Thomas", "A."),
family = "Gerds",
role = "aut",
email = "tag@biostat.ku.dk"),
person(given = c("Paul", "F."),
family = "Blanche",
role = "cre",
email = "paulfblanche@gmail.com"))
as necessary.- NOTE11 OK, 2 NOTE2026-10-25
- ERROR11 OK, 1 NOTE, 1 ERROR2026-10-24
- NOTE11 OK, 2 NOTE2026-06-09
- ERROR11 OK, 1 NOTE, 1 ERROR2026-06-08
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 3
- Examples that run
- 100%3 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
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- Help pages citing references
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Downloads
Dependencies
Installing wally adds 87 packages (43 with compiled code, 84 MB of source tarballs). Heaviest: stringi 11 MB, TH.data 8.2 MB, ggplot2 6.0 MB.
Code & Tests
Datasets
People & History
Maintainer since 1.0.8 (2017)
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- 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
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 1.0.10Latest
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- 1.0.92017-05-25 · diff ↗
- 1.0.82017-05-17
- RR 3.4.0 released · 2017-04-21
Package metadata
- First published
- 2017-05-17
- Total releases
- 3 / 9 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 2.9.0
- Bundled data
- 121 KB / 2 files
- Download size
- 72 KB
Cite
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