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101: Create hex logo for simIDM and prepare for CRAN release [skip vbump] (#102)
Co-authored-by: github-actions <41898282+github-actions[bot]@users.noreply.github.com>
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.github/workflows/check.yaml

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on:
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pull_request:
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types:
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- opened
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- synchronize
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- ready_for_review
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branches:
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- main
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- pre-release
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push:
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branches:
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- main
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- pre-release
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workflow_dispatch:
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jobs:
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audit:
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secrets:
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REPO_GITHUB_TOKEN: ${{ secrets.REPO_GITHUB_TOKEN }}
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linter:
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if: github.event_name != 'push'
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if: github.event_name == 'pull_request'
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name: SuperLinter 🦸‍♀️
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uses: insightsengineering/r.pkg.template/.github/workflows/linter.yaml@main
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roxygen:
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name: Roxygen 🅾
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uses: insightsengineering/r.pkg.template/.github/workflows/roxygen.yaml@main
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secrets:
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REPO_GITHUB_TOKEN: ${{ secrets.REPO_GITHUB_TOKEN }}
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with:
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auto-update: true
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gitleaks:
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name: gitleaks 💧
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uses: insightsengineering/r.pkg.template/.github/workflows/gitleaks.yaml@main
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spelling:
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if: github.event_name == 'pull_request'
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name: Spell Check 🆎
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uses: insightsengineering/r.pkg.template/.github/workflows/spelling.yaml@main
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secrets:
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REPO_GITHUB_TOKEN: ${{ secrets.REPO_GITHUB_TOKEN }}
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links:
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if: github.event_name != 'push'
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if: github.event_name == 'pull_request'
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name: Check URLs 🌐
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uses: insightsengineering/r.pkg.template/.github/workflows/links.yaml@main
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vbump:
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name: Version Bump 🤜🤛
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if: github.event_name == 'push' && github.ref == 'refs/heads/main'
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if: github.event_name == 'push'
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uses: insightsengineering/r.pkg.template/.github/workflows/version-bump.yaml@main
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secrets:
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REPO_GITHUB_TOKEN: ${{ secrets.REPO_GITHUB_TOKEN }}
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name: License Check 🃏
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uses: insightsengineering/r.pkg.template/.github/workflows/licenses.yaml@main
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style:
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if: github.event_name != 'push'
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if: github.event_name == 'pull_request'
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name: Style Check 👗
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uses: insightsengineering/r.pkg.template/.github/workflows/style.yaml@main
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with:
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auto-update: true
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grammar:
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if: github.event_name != 'push'
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name: Grammar Check 🔤
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uses: insightsengineering/r.pkg.template/.github/workflows/grammar.yaml@main

.github/workflows/docs.yaml

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push:
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branches:
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- main
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paths:
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- inst/templates/**
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- _pkgdown.*
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- DESCRIPTION
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- '**.md'
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- man/**
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- LICENSE.*
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- NAMESPACE
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pull_request:
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branches:
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- main
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- pre-release
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paths:
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- inst/templates/**
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- _pkgdown.*
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- DESCRIPTION
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- '**.md'
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- man/**
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- LICENSE.*
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- NAMESPACE
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workflow_dispatch:
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jobs:
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docs:
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name: Pkgdown Docs 📚
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uses: insightsengineering/r.pkg.template/.github/workflows/pkgdown.yaml@main
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secrets:
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REPO_GITHUB_TOKEN: ${{ secrets.REPO_GITHUB_TOKEN }}
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with:
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refs-order: c("latest-tag", "main")
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default-landing-page: latest-tag
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secrets:
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REPO_GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/post-release.yaml

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.github/workflows/release.yaml

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push:
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tags:
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- "v*"
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workflow_dispatch:
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jobs:
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release:
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name: Create release 🎉
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uses: insightsengineering/r.pkg.template/.github/workflows/release.yaml@main
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permissions:
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contents: write
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r-cmd:
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name: R CMD Check 🧬
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needs: [release, docs]
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uses: insightsengineering/r.pkg.template/.github/workflows/build-check-install.yaml@main
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secrets:
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REPO_GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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with:
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additional-r-cmd-check-params: --as-cran
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coverage:
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name: Coverage 📔
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needs: [release, docs]
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uses: insightsengineering/r.pkg.template/.github/workflows/test-coverage.yaml@main
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secrets:
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REPO_GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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build:
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name: Build package 🎁
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needs: release
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uses: insightsengineering/r.pkg.template/.github/workflows/build-check-install.yaml@main
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secrets:
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REPO_GITHUB_TOKEN: ${{ secrets.REPO_GITHUB_TOKEN }}
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REPO_GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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with:
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skip-r-cmd-check: true
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skip-r-cmd-install: true
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docs:
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name: Pkgdown Docs 📚
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needs: release
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uses: insightsengineering/r.pkg.template/.github/workflows/pkgdown.yaml@main
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secrets:
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REPO_GITHUB_TOKEN: ${{ secrets.REPO_GITHUB_TOKEN }}
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with:
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refs-order: c("latest-tag", "main")
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default-landing-page: latest-tag
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release:
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name: Create release 🎉
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uses: insightsengineering/r.pkg.template/.github/workflows/release.yaml@main
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secrets:
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REPO_GITHUB_TOKEN: ${{ secrets.REPO_GITHUB_TOKEN }}
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REPO_GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/scheduled.yaml

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---
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name: Scheduled 🕰️
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on:
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schedule:
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- cron: '45 3 * * 0'
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workflow_dispatch:
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jobs:
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cran-status:
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name: CRAN Status Monitor 📺
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uses: insightsengineering/r.pkg.template/.github/workflows/cran-status.yaml@main
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with:
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issue-assignees: "niessl,danielinteractive"

DESCRIPTION

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Type: Package
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Package: simIDM
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Title: Simulating Oncology Trials using an Illness-Death Model
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Version: 0.0.5.9026
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Version: 0.1.0
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Authors@R: c(
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person("Alexandra", "Erdmann", , "alexandra.erdmann@uni-ulm.de", role = c("aut", "cre")),
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person("Kaspar", "Rufibach", , "kaspar.rufibach@roche.com", role = "aut"),
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person("Holger", "Loewe", , "holger.loewe@roche.com", role = "aut"),
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person("Daniel", "Sabanes Bove", , "daniel.sabanes_bove@roche.com", role = "aut"),
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person("Holger", "Löwe", , "hbj.loewe@gmail.com", role = "aut"),
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person("Daniel", "Sabanés Bové", , "daniel.sabanes_bove@roche.com", role = "aut"),
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person("F. Hoffmann-La Roche AG", role = c("cph", "fnd")),
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person("University of Ulm", role = c("cph", "fnd"))
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)
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for random and event-driven censoring, an arbitrary number of
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treatment arms, staggered study entry and drop-out. Exponentially,
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Weibull and piecewise exponentially distributed survival times can be
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generated.
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generated. The correlation between PFS and OS can be calculated.
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License: Apache License 2.0
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URL: https://github.com/insightsengineering/simIDM/
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BugReports: https://github.com/insightsengineering/simIDM/issues

NEWS.md

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# simIDM 0.0.5.9026
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# simIDM 0.1.0
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### New Features
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- `prepareData` allows formatting of trial data for log-likelihood computation.
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- `estimateParams` estimates parameters of exponential and Weibull transition hazards for a given data set.
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- `estimateParams` estimates parameters of exponential and Weibull transition hazards using maximum likelihood for a given data set after using `prepareData`.
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- `corTrans` calculates the correlation between PFS and OS for a given set of transition hazards, and `corPFSOS` estimates this correlation for a given data set, optionally with a bootstrap based confidence interval.
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### Bug Fixes
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- `ExpSurvOS` now returns 0 instead of NaN for large values of t.
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- `WeibSurvOS` now does not return an error for large values of t.
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- `PWCSurvOS` now does not return an error for large values of t.
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- `PWCSurvOS` no longer returns values larger than 1, and is significantly faster, based on a closed form calculation instead of numerical integration.
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- `PWCSurvOS` now does not return an error for large values of t. It also no longer returns values larger than 1. It is significantly faster, based on a closed form calculation instead of numerical integration.
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- `getSimulatedData` now also works when there are no transitions from progression to death, similarly for `getOneClinicalTrial` (which now warns if there are no such transitions at all).
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### Miscellaneous
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- Renamed piecewise constant hazards function to `getPWCHazard` (previously `getPCWHazard`).
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- `PwcOSInt`, `integrateVector`, `WeibOSInteg` are no longer exported, and only used internally.
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- Renamed piecewise constant hazards function to `getPWCHazard` (previously `getPCWHazard`).
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# simIDM 0.0.5
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README.md

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<!-- markdownlint-disable-file -->
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<!-- README.md needs to be generated from README.Rmd. Please edit that file -->
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# simIDM
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# simIDM <img src="man/figures/logo.png" align="right" height="139" />
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<!-- badges: start -->
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The simulation set-up allows random and event-driven censoring, an
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arbitrary number of treatment arms, staggered study entry and drop-out.
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times can be generated.
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times can be generated. In addition, the correlation between PFS and OS
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can be calculated based on the simulation scenario, or estimated from a
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given data set.
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**Scope:**
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- Simulation of the illness-death model with constant, Weibull or
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piecewise constant transition hazards.
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- Conversion of the transition times to PFS and OS survival times.
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- Correlation between PFS and OS survival times can be calculated.
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**Main Features:**
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- Arbitrary number of treatment arms and flexible randomization ratio.
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- Staggered study entry.
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- Derivation of PFS and OS survival functions from transition hazards.
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- Correlation between PFS and OS can be estimated from a given data set.
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## Installation
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<!-- **CRAN** -->
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<!-- You can install the current stable version from CRAN with: -->
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<!-- ```{r cran-installation, eval = FALSE} -->
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<!-- install.packages("mmrm") -->
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<!-- ``` -->
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### Release
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**GitHub**
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You can install the current release version from *CRAN* with:
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You can install the current development version from GitHub with:
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``` r
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install.packages("simIDM")
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```
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### Development
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``` r
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## Getting Started
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See also the `quickstart` vignette or get started by trying out the
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example:
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See also the [quick
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start](https://insightsengineering.github.io/simIDM/latest-tag/articles/quickstart.html)
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vignette or get started by trying out this example:
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``` r
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library(simIDM)

README.rmd

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<!-- markdownlint-disable-file -->
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<!-- README.md needs to be generated from README.Rmd. Please edit that file -->
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# simIDM
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# simIDM <img src="man/figures/logo.png" align="right" height="139" />
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```{r, echo = FALSE}
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knitr::opts_chunk$set(
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endpoints OS and PFS based on the illness-death model, which can be used for trail planning, for example. The simulation
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set-up allows random and event-driven censoring, an arbitrary number of treatment arms, staggered study entry and drop-out.
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Exponentially, Weibull and piecewise exponentially distributed survival times can be generated.
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In addition, the correlation between PFS and OS can be calculated based on the simulation scenario, or estimated from a given data set.
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**Scope:**
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* Simulation of the illness-death model with constant, Weibull or piecewise constant transition hazards.
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* Conversion of the transition times to PFS and OS survival times.
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* Correlation between PFS and OS survival times can be calculated.
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**Main Features:**
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* Arbitrary number of treatment arms and flexible randomization ratio.
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* Staggered study entry.
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* Derivation of PFS and OS survival functions from transition hazards.
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* Correlation between PFS and OS can be estimated from a given data set.
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## Installation
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<!-- **CRAN** -->
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### Release
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<!-- You can install the current stable version from CRAN with: -->
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You can install the current release version from *CRAN* with:
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<!-- ```{r cran-installation, eval = FALSE} -->
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<!-- install.packages("mmrm") -->
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<!-- ``` -->
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```{r cran-installation, eval = FALSE}
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install.packages("simIDM")
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```
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**GitHub**
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### Development
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```{r gh-installation, eval = FALSE}
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## Getting Started
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```{r getting-started}
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```{r getting-started, results = 'hide'}
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library(simIDM)
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transitionGroup1 <- exponential_transition(h01 = 1.2, h02 = 1.5, h12 = 1.6)
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transitionGroup2 <- exponential_transition(h01 = 1, h02 = 1.3, h12 = 1.7)

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