Introduction | Example Dataset | Fit Initial Cox Model | Model-Free Tipping Point Analysis | Step-by-step walk through of the analyses using model-free imputation | Visualize Pooled Kaplan--Meier Curves | Visualize Tipping Point Graph | Summarize tipping point via Analysis Results Dataset (ARD) | Assess plausibility | Model-Based Tipping Point Analysis | Summary via Analysis Results Dataset (ARD) | Jump-to-Reference (J2R) as a Special Case of Model-based Imputation | Inspect the data | Fit the original Cox model | Run model-based imputation | J2R Results | References
Package: tipse 2.0
Ajmal Oodally
tipse: Tipping Point Analysis for Survival Endpoints
Implements tipping point sensitivity analysis for time-to-event endpoints under different missing data scenarios, as described in Oodally et al. (2025) <doi:10.48550/arXiv.2506.19988>. Supports both model-based and model-free imputation, multiple imputation workflows, plausibility assessment and visualizations. Enables robust assessment for regulatory and exploratory analyses.
Authors:
tipse_2.0.tar.gz
tipse_2.0.tar.gz(r-4.7-any)tipse_2.0.tar.gz(r-4.6-any)
tipse_2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tipse/json (API)
| # Install 'tipse' in R: |
| install.packages('tipse', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- codebreak200 - Patient level data from dummy trial
- extenet - Patient level data from dummy trial
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:03e6740944. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 185 | ||
| source / vignettes | OK | 230 | ||
| linux-release-x86_64 | OK | 193 | ||
| wasm-release | OK | 115 |
Exports:assess_plausibilityimpute_landmarkimpute_modelimpute_percentilepool_resultstipping_point_model_basedtipping_point_model_free
Dependencies:base64encbslibcachemclicpp11digestdplyrevaluatefarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhtmltoolsisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemimepillarpkgconfigpurrrR6rappdirsRColorBrewerrlangrmarkdownS7sassscalessurvivaltibbletidyselecttinytexutf8vctrsviridisLitewithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Assess Clinical Plausibility of Imputation Results | assess_plausibility |
| Patient level data from dummy trial | codebreak200 |
| Patient level data from dummy trial | extenet |
| Model-free imputation via landmark sampling | impute_landmark |
| Model-based imputation from parametric distributions | impute_model |
| Model-free imputation via percentile sampling | impute_percentile |
| Plot Pooled Kaplan–Meier Curves from Tipping Point Analysis | plot.tipse |
| Pooling results using Rubin's Rule | pool_results |
| Summarize Tipping Point Results (ARD Format) | summary.tipse |
| Tipping Point Analysis (Model-Based) | tipping_point_model_based |
| Tipping Point Analysis (Model-Free) | tipping_point_model_free |