Package: CoxAalenCR
Type: Package
Title: Additive-Multiplicative Cox-Aalen Subdistribution Hazard Model
        for Competing Risks
Version: 0.1.0
Authors@R: c(
    person(given = "Shikhar",
           family = "Tyagi",
           role = c("aut", "cre"),
           email = "shikhar1093tyagi@gmail.com",
           comment = c(ORCID = "0000-0003-1606-0844")),
    person(given = "Arvind",
           family = "Pandey",
           role = "aut",
           email = "arvindmzu@gmail.com"),
    person(given = "Bhupendra",
           family = "Singh",
           role = "aut",
           email = "bhupendra.rana@gmail.com"),
    person(given = "Vrijesh",
           family = "Tripathi",
           role = "aut",
           email = "vrijesh.tripathi@uwi.edu")
  )
Description: Implements the flexible additive-multiplicative Cox-Aalen
        subdistribution hazard regression model for competing risks
        data as proposed by Li and Long (2019)
        <doi:10.1007/s11424-019-7281-6>. The framework accommodates
        both time-varying non-parametric additive covariate effects
        through an Aalen (1980) additive model and constant
        multiplicative effects via a Cox proportional hazards
        structure, generalizing Scheike and Zhang (2002)
        <doi:10.1111/1467-9469.00065> and Martinussen and Scheike
        (2002) <doi:10.1093/biomet/89.2.283>. Includes inverse
        probability of censoring weighting (IPCW) with both
        Kaplan-Meier weights (Fine and Gray, 1999
        <doi:10.1080/01621459.1999.10474144>) and covariate-dependent
        Cox censoring weights (He et al., 2016
        <doi:10.1111/sjos.12172>; Li and Long, 2019
        <doi:10.1007/s11424-019-7281-6>). Provides simultaneous
        estimating equations based on Huffer and McKeague (1991)
        <doi:10.1080/01621459.1991.10475010>, asymptotic sandwich
        variance estimation with censoring-weight martingale
        corrections, cumulative incidence function (CIF) prediction
        with pointwise confidence intervals, supremum-type
        goodness-of-fit tests for time-varying covariate effects, and
        Monte Carlo competing risks data simulation.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices, utils, survival
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-09-21 09:41:26 UTC; root
Author: Shikhar Tyagi [aut, cre] (ORCID:
        <https://orcid.org/0000-0003-1606-0844>), Arvind Pandey [aut],
        Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: https://shikhartyagi.r-universe.dev
Date/Publication: 2026-08-21 15:20:02 UTC
RemoteUrl: https://github.com/cran/CoxAalenCR
RemoteRef: HEAD
RemoteSha: 37c06ad4be07bb25c3849421f4d4e6df796a9ce3