dreamer: Dose Response Models for Bayesian Model Averaging

Fits (longitudinal) dose-response models utilizing a Bayesian model averaging approach as outlined in Gould (2019) <doi:10.1002/bimj.201700211> for both continuous and binary responses. Functions for plotting and calculating various posterior quantities (e.g. posterior mean, quantiles, probability of minimum efficacious dose, etc.) are also implemented. Copyright Eli Lilly and Company (2019).

Version: 3.1.0
Imports: coda, dplyr (≥ 1.0.0), ellipsis (≥ 0.3), ggplot2, graphics, purrr, rootSolve, rjags (≥ 4-8), rlang (≥ 0.4.5), stats, tidyr (≥ 1.0.2), tidyselect (≥ 1.1)
Suggests: testthat (≥ 3.0), fs (≥ 1.5), knitr, rmarkdown, tibble, spelling
Published: 2022-09-01
Author: Richard Daniel Payne [aut, cre], William Michael Landau [rev], Mitch Thomann [rev], Eli Lilly and Company [cph]
Maintainer: Richard Daniel Payne <paynestatistics at gmail.com>
BugReports: https://github.com/rich-payne/dreamer/issues
License: MIT + file LICENSE
URL: https://github.com/rich-payne/dreamer
NeedsCompilation: no
Language: en-US
Materials: NEWS
CRAN checks: dreamer results

Documentation:

Reference manual: dreamer.pdf
Vignettes: dreamer
dreamer Methods

Downloads:

Package source: dreamer_3.1.0.tar.gz
Windows binaries: r-devel: dreamer_3.1.0.zip, r-release: dreamer_3.1.0.zip, r-oldrel: dreamer_3.1.0.zip
macOS binaries: r-release (arm64): dreamer_3.1.0.tgz, r-oldrel (arm64): dreamer_3.1.0.tgz, r-release (x86_64): dreamer_3.1.0.tgz
Old sources: dreamer archive

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