Package: casebase 0.10.6
casebase: Fitting Flexible Smooth-in-Time Hazards and Risk Functions via Logistic and Multinomial Regression
Fit flexible and fully parametric hazard regression models to survival data with single event type or multiple competing causes via logistic and multinomial regression. Our formulation allows for arbitrary functional forms of time and its interactions with other predictors for time-dependent hazards and hazard ratios. From the fitted hazard model, we provide functions to readily calculate and plot cumulative incidence and survival curves for a given covariate profile. This approach accommodates any log-linear hazard function of prognostic time, treatment, and covariates, and readily allows for non-proportionality. We also provide a plot method for visualizing incidence density via population time plots. Based on the case-base sampling approach of Hanley and Miettinen (2009) <doi:10.2202/1557-4679.1125>, Saarela and Arjas (2015) <doi:10.1111/sjos.12125>, and Saarela (2015) <doi:10.1007/s10985-015-9352-x>.
Authors:
casebase_0.10.6.tar.gz
casebase_0.10.6.zip(r-4.5)casebase_0.10.6.zip(r-4.4)casebase_0.10.6.zip(r-4.3)
casebase_0.10.6.tgz(r-4.4-any)casebase_0.10.6.tgz(r-4.3-any)
casebase_0.10.6.tar.gz(r-4.5-noble)casebase_0.10.6.tar.gz(r-4.4-noble)
casebase_0.10.6.tgz(r-4.4-emscripten)casebase_0.10.6.tgz(r-4.3-emscripten)
casebase.pdf |casebase.html✨
casebase/json (API)
NEWS
# Install 'casebase' in R: |
install.packages('casebase', repos = c('https://sahirbhatnagar.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/sahirbhatnagar/casebase/issues
- ERSPC - Data on the men in the European Randomized Study of Prostate Cancer Screening
- bmtcrr - Data on transplant patients
- brcancer - German Breast Cancer Study Group 2
- eprchd - Estrogen plus Progestin and the Risk of Coronary Heart Disease
- simdat - Simulated data under Weibull model with Time-Dependent Treatment Effect
- support - Study to Understand Prognoses Preferences Outcomes and Risks of Treatment
competing-riskscox-regressionregression-modelssurvival-analysis
Last updated 3 months agofrom:cbeba938cf. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 16 2024 |
R-4.5-win | OK | Oct 16 2024 |
R-4.5-linux | OK | Oct 16 2024 |
R-4.4-win | OK | Oct 16 2024 |
R-4.4-mac | OK | Oct 16 2024 |
R-4.3-win | OK | Oct 16 2024 |
R-4.3-mac | OK | Oct 16 2024 |
Exports:absoluteRiskabsoluteRisk.CompRiskcheckArgsEventIndicatorcheckArgsTimeEventfitSmoothHazardfitSmoothHazard.fithazardPlotpopTimeprepareXsampleCaseBasesummary
Dependencies:clicolorspacedata.tablefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalessurvivaltibbleutf8vctrsVGAMviridisLitewithr
Competing risk analysis
Rendered fromcompetingRisk.Rmd
usingknitr::rmarkdown
on Oct 16 2024.Last update: 2021-02-06
Started: 2016-02-27
Customizing Population Time Plots
Rendered fromcustomizingpopTime.Rmd
usingknitr::rmarkdown
on Oct 16 2024.Last update: 2020-07-03
Started: 2020-03-03
Introduction to casebase sampling
Rendered fromsmoothHazard.Rmd
usingknitr::rmarkdown
on Oct 16 2024.Last update: 2021-02-06
Started: 2016-01-06
Plot Cumulative Incidence and Survival Curves
Rendered fromplotabsRisk.Rmd
usingknitr::rmarkdown
on Oct 16 2024.Last update: 2020-06-30
Started: 2020-06-29
Plot Hazards and Hazard Ratios
Rendered fromplotsmoothHazard.Rmd
usingknitr::rmarkdown
on Oct 16 2024.Last update: 2024-02-01
Started: 2020-06-19
Population Time Plots
Rendered frompopTime.Rmd
usingknitr::rmarkdown
on Oct 16 2024.Last update: 2021-10-19
Started: 2016-03-02
Time-Varying Covariates
Rendered fromtime-varying-covariates.Rmd
usingknitr::rmarkdown
on Oct 16 2024.Last update: 2023-08-03
Started: 2023-08-03