survPen
2.0.5Multidimensional Penalized Splines for (Excess) Hazard Models, Relative Mortality Ratio Models and Marginal Intensity Models
Overview
Fits (excess) hazard, relative mortality ratio or marginal intensity models with multidimensional penalized splines allowing for time-dependent effects, non-linear effects and interactions between several continuous covariates. In survival and net survival analysis, in addition to modelling the effect of time (via the baseline hazard), one has often to deal with several continuous covariates and model their functional forms, their time-dependent effects, and their interactions. Model specification becomes therefore a complex problem and penalized regression splines represent an appealing solution to that problem as splines offer the required flexibility while penalization limits overfitting issues. Current implementations of penalized survival models can be slow or unstable and sometimes lack some key features like taking into account expected mortality to provide net survival and excess hazard estimates. In contrast, survPen provides an automated, fast, and stable implementation (thanks to explicit calculation of the derivatives of the likelihood) and offers a unified framework for multidimensional penalized hazard and excess hazard models. Later versions (>2.0.0) include penalized models for relative mortality ratio, and marginal intensity in recurrent event setting. survPen may be of interest to those who 1) analyse any kind of time-to-event data: mortality, disease relapse, machinery breakdown, unemployment, etc 2) wish to describe the associated hazard and to understand which predictors impact its dynamics, 3) wish to model the relative mortality ratio between a cohort and a reference population, 4) wish to describe the marginal intensity for recurrent event data. See Fauvernier et al. (2019a) doi:10.21105/joss.01434 for an overview of the package and Fauvernier et al. (2019b) doi:10.1111/rssc.12368 for the method.
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- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-06-0712 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-04-2512 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-04-2212 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 2 earlier snapshots
- ERROR2026-04-1811 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 96%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 13%
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People & History
15 releases. Pick two to compare their code metrics. R releases are shown for context.
- 2.0.5Latest
- 2.0.42026-05-09 · diff ↗
- RR 4.6.0 released · 2026-04-24
- 2.0.32026-03-20 · diff ↗
- RR 4.5.0 released · 2025-04-11
- 2.0.22025-03-08 · diff ↗
- 2.0.12025-01-21 · diff ↗
- 2.0.02024-12-02 · diff ↗
- RR 4.4.0 released · 2024-04-24
- 1.6.02023-09-14 · diff ↗
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 1.5.22021-09-11 · diff ↗
- RR 4.1.0 released · 2021-05-18
- 1.5.12020-09-25 · diff ↗
- 1.5.02020-05-25 · diff ↗
Package metadata
- First published
- 2019-02-27
- Total releases
- 15 / 7 yrs
- License
- GPL-3 | file LICENSE OSI
- Minimum R
- ≥ 4.0.0
- Bundled data
- 148 KB / 4 files
- Download size
- 1.1 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet