Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
-
○Academic publication links
-
○Committers with academic emails
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (15.1%) to scientific vocabulary
Keywords
Repository
Simulation Engine for Multistate Models
Basic Info
- Host: GitHub
- Owner: insightsengineering
- Language: R
- Default Branch: main
- Homepage: https://insightsengineering.github.io/simIDM/
- Size: 4.04 MB
Statistics
- Stars: 13
- Watchers: 6
- Forks: 2
- Open Issues: 0
- Releases: 2
Topics
Metadata Files
README.md
simIDM 
<!-- badges: end -->
Survival multistate models are a powerful and flexible tool for modeling and analyzing complex time-to-event data. The three-state illness-death model can be used to jointly model the oncology endpoints progression-free survival (PFS) and overall survival (OS). Jointly modeling the endpoints PFS and OS with the illness-death model has the major advantage of both adequately accounting for the correlation of the two endpoints and eliminating the need of the strong assumption of proportional hazards. This package provides the tools to simulate a large number of clinical trials with endpoints OS and PFS based on the illness-death model, which can be used for trail planning, for example. The simulation set-up allows random and event-driven censoring, an arbitrary number of treatment arms, staggered study entry and drop-out. Exponentially, Weibull and piecewise exponentially distributed survival times can be generated. In addition, the correlation between PFS and OS can be calculated based on the simulation scenario, or estimated from a given data set.
Scope:
- Simulation of the illness-death model with constant, Weibull or piecewise constant transition hazards.
- Conversion of the transition times to PFS and OS survival times.
- Correlation between PFS and OS survival times can be calculated.
Main Features:
- Exponentially, Weibull and piecewise exponentially distributed survival times.
- Random censoring and event-driven censoring after a pre-specified number of PFS or OS events.
- Arbitrary number of treatment arms and flexible randomization ratio.
- Staggered study entry.
- Derivation of PFS and OS survival functions from transition hazards.
- Correlation between PFS and OS can be estimated from a given data set.
Installation
Release
You can install the current release version from CRAN with:
r
install.packages("simIDM")
Development
You can install the current development version from GitHub with:
r
if (!require("remotes")) {
install.packages("remotes")
}
remotes::install_github("insightsengineering/simIDM")
Getting Started
See also the quick start vignette or get started by trying out this example:
``` r library(simIDM) transitionGroup1 <- exponentialtransition(h01 = 1.2, h02 = 1.5, h12 = 1.6) transitionGroup2 <- exponentialtransition(h01 = 1, h02 = 1.3, h12 = 1.7)
simStudies <- getClinicalTrials( nRep = 100, nPat = c(50, 50), seed = 1234, datType = "1rowPatient", transitionByArm = list(transitionGroup1, transitionGroup2), dropout = list(rate = 0.1, time = 12), accrual = list(param = "intensity", value = 12) ) ```
We get as output a list with nRep elements, each containing a data set
of a single simulated trial.
``` r head(simStudies[[1]])
> id trt PFStime CensoredPFS PFSevent OStime CensoredOS OSevent
> 1 1 1 0.08087899 0 1 2.0330026 0 1
> 2 2 1 0.84758881 0 1 0.8475888 0 1
> 3 3 1 0.18276912 0 1 0.1968048 0 1
> 4 4 1 0.13789870 0 1 1.2899802 0 1
> 5 5 1 0.06458797 0 1 0.6901351 0 1
> 6 6 1 0.83894555 0 1 1.0709457 0 1
> recruitTime OStimeCal PFStimeCal
> 1 0.8516769 2.884679 0.9325558
> 2 4.1068045 4.954393 4.9543933
> 3 2.3596282 2.556433 2.5423973
> 4 1.1682298 2.458210 1.3061285
> 5 0.7710655 1.461201 0.8356535
> 6 3.1585892 4.229535 3.9975347
```
Citing simIDM
To cite simIDM please see
here.
Owner
- Name: Roche/Genentech - Insights Engineering
- Login: insightsengineering
- Kind: organization
- Location: Switzerland
- Website: https://code4life.roche.com/
- Repositories: 53
- Profile: https://github.com/insightsengineering
Roche/Genentech - Insights Engineering
GitHub Events
Total
- Issues event: 4
- Watch event: 2
- Delete event: 4
- Issue comment event: 6
- Push event: 17
- Pull request review event: 3
- Pull request event: 2
- Fork event: 2
- Create event: 4
Last Year
- Issues event: 4
- Watch event: 2
- Delete event: 4
- Issue comment event: 6
- Push event: 17
- Pull request review event: 3
- Pull request event: 2
- Fork event: 2
- Create event: 4
Committers
Last synced: over 3 years ago
All Time
- Total Commits: 69
- Total Committers: 11
- Avg Commits per committer: 6.273
- Development Distribution Score (DDS): 0.667
Top Committers
| Name | Commits | |
|---|---|---|
| Daniel Sabanes Bove | d****e@u****m | 23 |
| niessl | 6****l@u****m | 16 |
| niessl | n****l@u****m | 15 |
| walkowif | 5****f@u****m | 4 |
| Dinakar | 2****9@u****m | 3 |
| walkowif | w****f@u****m | 3 |
| Kaspar Rufibach | 4****7@u****m | 1 |
| dinakar29 | d****9@u****m | 1 |
| arkadiuszbeer | 8****r@u****m | 1 |
| arkadiuszbeer | a****r@u****m | 1 |
| cicdguy | c****y@u****m | 1 |
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 42
- Total pull requests: 72
- Average time to close issues: about 2 months
- Average time to close pull requests: 8 days
- Total issue authors: 8
- Total pull request authors: 8
- Average comments per issue: 0.52
- Average comments per pull request: 2.76
- Merged pull requests: 71
- Bot issues: 1
- Bot pull requests: 0
Past Year
- Issues: 2
- Pull requests: 2
- Average time to close issues: about 2 months
- Average time to close pull requests: 27 days
- Issue authors: 2
- Pull request authors: 2
- Average comments per issue: 2.0
- Average comments per pull request: 3.5
- Merged pull requests: 2
- Bot issues: 1
- Bot pull requests: 0
Top Authors
Issue Authors
- danielinteractive (16)
- holgstr (11)
- niessl (9)
- numbersman77 (2)
- HenrikBengtsson (1)
- nguyenducanhvn101087 (1)
- github-actions[bot] (1)
- moncham1 (1)
Pull Request Authors
- holgstr (20)
- danielinteractive (19)
- niessl (17)
- walkowif (13)
- llrs-roche (2)
- arkadiuszbeer (1)
- numbersman77 (1)
- cicdguy (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- cran 190 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 2
- Total maintainers: 1
cran.r-project.org: simIDM
Simulating Oncology Trials using an Illness-Death Model
- Homepage: https://github.com/insightsengineering/simIDM/
- Documentation: http://cran.r-project.org/web/packages/simIDM/simIDM.pdf
- License: Apache License 2.0
-
Latest release: 0.1.0
published over 2 years ago
Rankings
Maintainers (1)
Dependencies
- R >= 3.6 depends
- checkmate * imports
- stats * imports
- coxphw * suggests
- knitr * suggests
- mvna * suggests
- prodlim * suggests
- rmarkdown * suggests
- survival * suggests
- testthat >= 2.0 suggests