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This package was removed from CRAN on 2025-03-21. Its history is shown below.
Reason: issues were not corrected in time
Details below reflect version 0.4.4, its last release before removal.

miWQS

0.4.4

Multiple Imputation Using Weighted Quantile Sum Regression

0packages depend
downloads / year
test coverage
checks pass

Overview

About
Maintained by Paul M. Hargarten5 releasesCRAN page ↗

The miWQS package handles the uncertainty due to below the detection limit in a correlated component mixture problem. Researchers want to determine if a set/mixture of continuous and correlated components/chemicals is associated with an outcome and if so, which components are important in that mixture. These components share a common outcome but are interval-censored between zero and low thresholds, or detection limits, that may be different across the components. This package applies the multiple imputation (MI) procedure to the weighted quantile sum regression (WQS) methodology for continuous, binary, or count outcomes (Hargarten & Wheeler (2020) doi:10.1016/j.envres.2020.109466). The imputation models are: bootstrapping imputation (Lubin et.al (2004) doi:10.1289/ehp.7199), univariate Bayesian imputation (Hargarten & Wheeler (2020) doi:10.1016/j.envres.2020.109466), and multivariate Bayesian regression imputation.

Install

Health

CRAN checks

CRAN check results are not tracked yet.

Code health
Yes
Tests · ratio 0.02
not tracked
Coverage
100%
Documentation · exports
22
Dependencies · direct

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
94%
Documented parameters
96%
Return-value docs
92%
References docs
29%

Downloads

Daily download trend is not available in this view yet.
Also on82 r2u57 c2d4u

Dependencies

Declared dependencies
28 external dependencies (excludes base and recommended)
Depends (5)
R >= 3.5.0methodsparallelstatsutils
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
indirect (not tracked)

Nothing depends on this yet.

Code & Tests

People & History

People (2)
Maintainer (1)
Author, Maintainer
Authors (2)
Author, Maintainer
Author, Reviewer, Thesis advisor
Reviewers (1)
Author, Reviewer, Thesis advisor
Package Timeline

5 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.5.0 released · 2025-04-11
  • archivedRemoved from CRAN
    2025-03-21
    issues were not corrected in time
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • 0.4.4
    2021-04-02 · diff ↗
  • 0.4.2
    2021-01-21 · diff ↗
  • R
    R 4.0.0 released · 2020-04-24
  • 0.2.0
    2019-12-12 · diff ↗
  • 0.1.0
    2019-07-31 · diff ↗
  • R
    R 3.6.0 released · 2019-04-26
  • 0.0.9
    2018-12-23
  • R
    R 3.5.0 released · 2018-04-23

Package metadata

Total releases
5
License
GPL-3 OSI
Minimum R
≥ 3.5.0
Bundled data
115 KB / 2 files
Download size
not tracked yet
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("miWQS")
Hargarten, P. M., & Wheeler, D. C. (n.d.). miWQS: Multiple Imputation Using Weighted Quantile Sum Regression (Version 0.4.4) [Computer software]. Retrieved August 13, 2026, from https://CRAN.R-project.org/package=miWQS

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

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

APA

Balamuta, J. J. (2026). R Observatory: Metrics for miWQS version 0.4.4 [Data set]. HJJB, LLC. Data release v2026-08-11. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-11, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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