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:Sahir Bhatnagar [aut, cre], Maxime Turgeon [aut], Jesse Islam [aut], Olli Saarela [aut], James Hanley [aut]

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casebase/json (API)
NEWS

# Install 'casebase' in R:
install.packages('casebase', repos = c('https://sahirbhatnagar.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/sahirbhatnagar/casebase/issues

Datasets:
  • 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

On CRAN:

competing-riskscox-regressionregression-modelssurvival-analysis

7.33 score 9 stars 87 scripts 1.3k downloads 11 exports 31 dependencies

Last updated 3 months agofrom:cbeba938cf. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 16 2024
R-4.5-winOKOct 16 2024
R-4.5-linuxOKOct 16 2024
R-4.4-winOKOct 16 2024
R-4.4-macOKOct 16 2024
R-4.3-winOKOct 16 2024
R-4.3-macOKOct 16 2024

Exports:absoluteRiskabsoluteRisk.CompRiskcheckArgsEventIndicatorcheckArgsTimeEventfitSmoothHazardfitSmoothHazard.fithazardPlotpopTimeprepareXsampleCaseBasesummary

Dependencies:clicolorspacedata.tablefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalessurvivaltibbleutf8vctrsVGAMviridisLitewithr

Competing risk analysis

Rendered fromcompetingRisk.Rmdusingknitr::rmarkdownon Oct 16 2024.

Last update: 2021-02-06
Started: 2016-02-27

Customizing Population Time Plots

Rendered fromcustomizingpopTime.Rmdusingknitr::rmarkdownon Oct 16 2024.

Last update: 2020-07-03
Started: 2020-03-03

Introduction to casebase sampling

Rendered fromsmoothHazard.Rmdusingknitr::rmarkdownon Oct 16 2024.

Last update: 2021-02-06
Started: 2016-01-06

Plot Cumulative Incidence and Survival Curves

Rendered fromplotabsRisk.Rmdusingknitr::rmarkdownon Oct 16 2024.

Last update: 2020-06-30
Started: 2020-06-29

Plot Hazards and Hazard Ratios

Rendered fromplotsmoothHazard.Rmdusingknitr::rmarkdownon Oct 16 2024.

Last update: 2024-02-01
Started: 2020-06-19

Population Time Plots

Rendered frompopTime.Rmdusingknitr::rmarkdownon Oct 16 2024.

Last update: 2021-10-19
Started: 2016-03-02

Time-Varying Covariates

Rendered fromtime-varying-covariates.Rmdusingknitr::rmarkdownon Oct 16 2024.

Last update: 2023-08-03
Started: 2023-08-03