R Observatory: Metrics for sievePH version 1.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

sievePH

1.1Package record

Sieve Analysis Methods for Proportional Hazards Models

0packages depend

2.7Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Michal JuraskaCRAN page ↗GitHub ↗Issues ↗

Implements a suite of semiparametric and nonparametric kernel-smoothed estimation and testing procedures for continuous mark-specific stratified hazard ratio (treatment/placebo) models in a randomized treatment efficacy trial with a time-to-event endpoint. Semiparametric methods, allowing multivariate marks, are described in Juraska M and Gilbert PB (2013), Mark-specific hazard ratio model with multivariate continuous marks: an application to vaccine efficacy. Biometrics 69(2):328-337 doi:10.1111/biom.12016, and in Juraska M and Gilbert PB (2016), Mark-specific hazard ratio model with missing multivariate marks. Lifetime Data Analysis 22(4):606-25 doi:10.1007/s10985-015-9353-9. Nonparametric kernel-smoothed methods, allowing univariate marks only, are described in Sun Y and Gilbert PB (2012), Estimation of stratified mark‐specific proportional hazards models with missing marks. Scandinavian Journal of Statistics}, 39(1):34-52 doi:10.1111/j.1467-9469.2011.00746.x, and in Gilbert PB and Sun Y (2015), Inferences on relative failure rates in stratified mark-specific proportional hazards models with missing marks, with application to human immunodeficiency virus vaccine efficacy trials. Journal of the Royal Statistical Society Series C: Applied Statistics, 64(1):49-73 doi:10.1111/rssc.12067. Both semiparametric and nonparametric approaches consider two scenarios: (1) the mark is fully observed in all subjects who experience the event of interest, and (2) the mark is subject to missingness-at-random in subjects who experience the event of interest. For models with missing marks, estimators are implemented based on (i) inverse probability weighting (IPW) of complete cases (for the semiparametric framework), and (ii) augmentation of the IPW estimating functions by leveraging correlations between the mark and auxiliary data to 'impute' the augmentation term for subjects with missing marks (for both the semiparametric and nonparametric framework). The augmented IPW estimators are doubly robust and recommended for use with incomplete mark data. The semiparametric methods make two key assumptions: (i) the time-to-event is assumed to be conditionally independent of the mark given treatment, and (ii) the weight function in the semiparametric density ratio/biased sampling model is assumed to be exponential. Diagnostic testing procedures for evaluating validity of both assumptions are implemented. Summary and plotting functions are provided for estimation and inferential results.

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("sievePH", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("mjuraska/sievePH")

Development version from mjuraska/sievePH. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-sieveph

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-sievePH

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-sievePH

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 4.6 min · r-devel-windows-x86_64

Status changes

OK13 OK2026-08-04
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09
ERROR12 OK, 1 ERROR2026-06-08
OK14 OK2026-04-22

Show 2 earlier changesHide 2 earlier changes

ERROR13 OK, 1 ERROR2026-04-18
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.1

READMEYes · 186 wordsVignettesNoNEWSYes · 0% structuredCitation fileNoWebsitenot declared in DESCRIPTION

Help pages: 11
Examples that run: 100%11 run in a plain check
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 82%

How these are measured

Downloads

2.7K

CRAN downloads in the past year

Rank #14,520 · ~7/day · ~224/mo

Releases R versions

Daily download trend is not available in this view yet.

25230 days

82790 days

2.7K1 year

Compare downloads with other packages →

Also on361 r2u3 autocran89 c2d4u

How downloads are counted

Repository

mjuraska/sieveph ↗Account: mjuraska

0Stars

0Forks

0Open issues

0Open PRs

0Releases

Last activity 2026-01-14 · Default branch at 1.2, ahead of CRAN 1.1 (checked 2026-10-21)

Responsiveness

not measured

How these are measured

PracticesBeta

Checks run against github.com/mjuraska/sieveph on 2026-10-21.

No development-tooling practices detected in the upstream repository.

How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies

7 external dependencies (excludes base and recommended)

Installing sievePH adds 73 packages (38 with compiled code, 71 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, doBy 4.3 MB.

Depends (0)

none

Imports (8)

graphicsstatssurvivalggplot2 ggpubr scales plyr np

LinkingTo (2)

Rcpp RcppArmadillo

Suggests (0)

none

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (3)

Michal Juraska

Author, Maintainer since 1.0.0 (2019)

Li Li

Contributor · added in 1.0.4

Stephanie Wu

Contributor

Releases (5)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
1.1Latest
record
2024-05-18 · current release · diff ↗ ·
added 2 exports
kernel_sievePH, kernel_sievePHaipw
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
1.0.4
record
2023-02-03 · diff ↗ ·
added 1 export
ggplot_sieve
1.0.3
record
2022-08-16 · diff ↗
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
R
R 4.0.0 released · 2020-04-24
1.0.1
record
2019-12-06 · diff ↗
R
R 3.6.0 released · 2019-04-26
1.0.0
record
2019-02-26
R
R 3.5.0 released · 2018-04-23

Package metadata

First published: 2019-02-26
Total releases: 5 / 7 yrs
License: GPL-2 OSI
Download size: 66 KB

Appears in task views

Missing Data

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("sievePH")

Format

Juraska, M., Li, L., & Wu, S. (2024). sievePH: Sieve Analysis Methods for Proportional Hazards Models (Version 1.1) [Computer software]. https://doi.org/10.32614/CRAN.package.sievePH

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for sievePH version 1.1 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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