Package: mhazard 0.2.3

mhazard: Nonparametric and Semiparametric Methods for Multivariate Failure Time Data

Nonparametric survival function estimates and semiparametric regression for the multivariate failure time data with right-censoring. For nonparametric survival function estimates, the Volterra, Dabrowska, and Prentice-Cai estimates for bivariate failure time data may be computed as well as the Dabrowska estimate for the trivariate failure time data. Bivariate marginal hazard rate regression can be fitted for the bivariate failure time data. Functions are also provided to compute (bootstrap) confidence intervals and plot the estimates of the bivariate survival function. For details, see "The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach", Prentice, R., Zhao, S. (2019, ISBN: 978-1-4822-5657-4), CRC Press.

Authors:Eric Bair [aut, cre], Taylor Petty [aut], Shanshan Zhao [aut]

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mhazard.pdf |mhazard.html
mhazard/json (API)
NEWS

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

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • anemia - Aplastic anemia clinical trial data.
  • bladder - Bladder tumor recurrence data.
  • clayton_sim - Simulated Clayton-Oakes data.

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 scripts 195 downloads 11 exports 9 dependencies

Last updated 1 years agofrom:25b8c63695. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 25 2024
R-4.5-win-x86_64OKOct 25 2024
R-4.5-linux-x86_64OKOct 25 2024
R-4.4-win-x86_64OKOct 25 2024
R-4.4-mac-x86_64OKOct 25 2024
R-4.4-mac-aarch64OKOct 25 2024
R-4.3-win-x86_64OKOct 25 2024
R-4.3-mac-x86_64OKOct 25 2024
R-4.3-mac-aarch64OKOct 25 2024

Exports:genClayton2genClayton3genClaytonRegmHR2mHR2.LFmHR2.tvcnpSurv2npSurv3plotnpSurv2.3DplotnpSurv2.HMtvc.example

Dependencies:bootlatticeMatrixmisc3dplot3DRcppRcppArmadillorootSolvesurvival