R (>= 2.0.0), alr3, lattice, magic, MASS, nlme, plotrix

R (>= 2.0.0), lattice, magic, MASS, nlme, plotrix, methods

R (>= 2.0.0), alr3, lattice, magic, MASS, nlme, plotrix,
methods

R (>= 2.0.0), alr3, gtools, lattice, magic, MASS, nlme,
plotrix, methods, stats4

R (>= 2.0.0), alr3, gtools, lattice, magic, MASS, nlme,
plotrix, methods, stats, stats4
Analysis of dose-response curves in biology, environmental
sciences, medicine, pharmacology, toxicology

Christian Ritz <ritz@bioassay.dk>, Jens Strebig <jcs@life.ku.dk>
R (>= 2.0.0), car, gtools, MASS, magic, methods, plotrix,
stats
Analysis of dose-response curves in biology, environmental sciences, medicine, pharmacology, toxicology

Christian Ritz <ritz@bioassay.dk>, Jens C. Strebig <streibig@bioassay.dk>
Analysis of dose-response data is made available through a suite of flexible and versatile model fitting and after-fitting functions.

c(
person(
given = "Alberto",
family = "Pessia",
email = "dev@albertopessia.com",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0001-8607-9191")
),
person(
given = "Alina",
family = "Malyutina",
role = "ctb",
comment = c(ORCID = "0000-0001-8220-5859")
)
)
Fit logistic functions to observed dose-response data and evaluate
goodness of fit measures. See Malyutina A., Tang J., and Pessia A. (2021)
<doi:10.1101/2021.06.07.447323>.
Alberto Pessia [aut, cre] (<https://orcid.org/0000-0001-8607-9191>),
Alina Malyutina [ctb] (<https://orcid.org/0000-0001-8220-5859>)

c(
person("Alberto", "Pessia", , "dev@albertopessia.com", role = c("aut", "cre"),
comment = c(ORCID = "0000-0001-8607-9191")),
person("Alina", "Malyutina", role = "ctb",
comment = c(ORCID = "0000-0001-8220-5859"))
)
Fit logistic functions to observed dose-response continuous
data and evaluate goodness-of-fit measures. See Malyutina A., Tang J.,
and Pessia A. (2021) <doi:10.1101/2021.06.07.447323>.
knitr, rmarkdown, spelling, testthat (>= 3.1.0)

Dose Response Models for Bayesian Model Averaging
c(
person(given = "Richard",
family = "Payne",
role = c("aut", "cre"),
email = "paynestatistics@gmail.com"),
person(given = "William Michael",
family = "Landau",
role = c("rev"),
email = "will.landau@gmail.com"),
person("Mitch", "Thomann",
role = c("rev"),
email = "mitchell.thomann@lilly.com"),
person(family = "Eli Lilly and Company",
role = "cph"))
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).
coda, dplyr (>= 1.0.0), ggplot2, graphics, purrr, rootSolve,
rjags (>= 4-8), rlang (>= 0.4.5), stats, tidyr (>= 1.0.2),
tidyselect (>= 1.1)
testthat (>= 3.0), fs (>= 1.5), knitr, rmarkdown, tibble,
spelling
Richard Payne [aut, cre],
William Michael Landau [rev],
Mitch Thomann [rev],
Eli Lilly and Company [cph]