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ameras: Analyze Multiple Exposure Realizations in Association Studies

Analyze association studies with multiple realizations of a noisy or uncertain exposure. These can be obtained from e.g. a two-dimensional Monte Carlo dosimetry system (Simon et al 2015 <doi:10.1667/RR13729.1>) to characterize exposure uncertainty. The implemented methods are regression calibration (Carroll et al. 2006 <doi:10.1201/9781420010138>), extended regression calibration (Little et al. 2023 <doi:10.1038/s41598-023-42283-y>), Monte Carlo maximum likelihood (Stayner et al. 2007 <doi:10.1667/RR0677.1>), frequentist model averaging (Kwon et al. 2023 <doi:10.1371/journal.pone.0290498>), and Bayesian model averaging (Kwon et al. 2016 <doi:10.1002/sim.6635>). Supported model families are Gaussian, binomial, multinomial, Poisson, proportional hazards, and conditional logistic.

Version: 0.1.1
Depends: R (≥ 3.5.0), stats, nimble
Imports: Rcpp (≥ 1.0.10), RcppEigen, coda, numDeriv, MCMCvis, mvtnorm, memoise, methods
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), ggplot2
Published: 2026-03-29
DOI: 10.32614/CRAN.package.ameras
Author: Sander Roberti ORCID iD [aut, cre], William Wheeler [aut], Deukwoo Kwon ORCID iD [aut], Ruth Pfeiffer ORCID iD [ctb], NCI [cph, fnd]
Maintainer: Sander Roberti <sander.roberti at nih.gov>
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: README, NEWS
CRAN checks: ameras results

Documentation:

Reference manual: ameras.html , ameras.pdf
Vignettes: Confidence intervals (source, R code)
Fitting models and displaying output (source, R code)
Relative risk models (source, R code)
Parameter transformations (source, R code)

Downloads:

Package source: ameras_0.1.1.tar.gz
Windows binaries: r-devel: ameras_0.1.1.zip, r-release: ameras_0.1.1.zip, r-oldrel: ameras_0.1.1.zip
macOS binaries: r-release (arm64): ameras_0.1.1.tgz, r-oldrel (arm64): not available, r-release (x86_64): ameras_0.1.1.tgz, r-oldrel (x86_64): ameras_0.1.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ameras to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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