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Merge pull request #71 from openpharma/mmrm_comparison
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New vignette: exemplary comparison of Bayesian and frequentist MMRM fits
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@wlandau
wlandau authored Nov 14, 2023
2 parents 1652e71 + 6fb042a commit fe8f4d6
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1 change: 1 addition & 0 deletions .Rbuildignore
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^\.lintr$
^_pkgdown\.yml$
^docs$
^data-raw$
77 changes: 28 additions & 49 deletions DESCRIPTION
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Package: brms.mmrm
Title: Bayesian MMRMs using 'brms'
Description: The mixed model for repeated measures (MMRM) is a
popular model for longitudinal clinical trial data with
continuous endpoints, and 'brms' is a powerful and versatile
package for fitting Bayesian regression models.
The 'brms.mmrm' R package leverages 'brms' to run MMRMs, and
it supports a simplified interfaced to reduce difficulty
and align with the best practices of the life sciences.
References: Bürkner (2017) <doi:10.18637/jss.v080.i01>,
Mallinckrodt (2008) <doi:10.1177/009286150804200402>.
Version: 0.0.2.9001
Authors@R: c(
person(c("William", "Michael"), "Landau", , "[email protected]", role = c("aut", "cre"),
comment = c(ORCID = "0000-0003-1878-3253")),
person("Kevin", "Kunzmann", , "[email protected]", role = "aut",
comment = c(ORCID = "0000-0002-1140-7143")),
person("Yoni", "Sidi", , "[email protected]", role = "aut"),
person("Christian", "Stock", , "[email protected]", role = "aut",
comment = c(ORCID = "0000-0002-3493-3234")),
person(, "Eli Lilly and Company", role = c("cph", "fnd")),
person("Boehringer Ingelheim Pharma GmbH & Co. KG", role = c("cph", "fnd"))
)
Description: The mixed model for repeated measures (MMRM) is a popular
model for longitudinal clinical trial data with continuous endpoints,
and 'brms' is a powerful and versatile package for fitting Bayesian
regression models. The 'brms.mmrm' R package leverages 'brms' to run
MMRMs, and it supports a simplified interfaced to reduce difficulty
and align with the best practices of the life sciences. References:
Bürkner (2017) <doi:10.18637/jss.v080.i01>, Mallinckrodt (2008)
<doi:10.1177/009286150804200402>.
License: MIT + file LICENSE
URL:
https://openpharma.github.io/brms.mmrm/,
URL: https://openpharma.github.io/brms.mmrm/,
https://github.com/openpharma/brms.mmrm
BugReports: https://github.com/openpharma/brms.mmrm/issues
Authors@R: c(
person(
given = c("William", "Michael"),
family = "Landau",
role = c("aut", "cre"),
email = "[email protected]",
comment = c(ORCID = "0000-0003-1878-3253")
),
person(
given = "Kevin",
family = "Kunzmann",
role = "aut",
email = "[email protected]",
comment = c(ORCID = "0000-0002-1140-7143")
),
person(
given = "Yoni",
family = "Sidi",
role = "aut",
email = "[email protected]"
),
person(
given = "Christian",
family = "Stock",
role = "aut",
email = "[email protected]",
comment = c(ORCID = "0000-0002-3493-3234")
),
person(
family = "Eli Lilly and Company",
role = c("cph", "fnd")
),
person(
"Boehringer Ingelheim Pharma GmbH & Co. KG",
role = c("cph", "fnd")
))
Depends:
R (>= 4.0.0)
Imports:
Expand All @@ -73,18 +46,24 @@ Imports:
zoo
Suggests:
BH,
gt,
gtsummary,
knitr (>= 1.30),
markdown (>= 1.1),
mmrm,
parallel,
Rcpp,
RcppEigen,
RcppParallel,
rmarkdown (>= 2.4),
rstan,
StanHeaders,
testthat (>= 3.0.0)
VignetteBuilder:
knitr
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
VignetteBuilder: knitr
Config/testthat/edition: 3
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
LazyData: true
10 changes: 6 additions & 4 deletions R/brm_package.R
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#' it supports a simplified interfaced to reduce difficulty
#' and align with the best practices of the life sciences.
#' @references
#' * Paul-Christian Bürkner (2017). brms: An R Package for Bayesian
#' * Bürkner PC (2017). brms: An R Package for Bayesian
#' Multilevel Models Using Stan.
#'. Journal of Statistical Software, 80(1), 1-28.
#'. J Stat Softw, 80(1), 1-28.
#' doi:10.18637/jss.v080.i01
#' * Mallinckrodt, C.H., Lane, P.W., Schnell, D. et al.
#' * Mallinckrodt CH, Lane PW, Schnell D, et al (2008).
#' Recommendations for the Primary Analysis of Continuous Endpoints
#' in Longitudinal Clinical Trials.
#' Ther Innov Regul Sci 42, 303–319 (2008).
#' Ther Innov Regul Sci, 42, 303–319.
#' doi:10.1177/009286150804200402
#' * Mallinckrodt C and Lipkovich I (2017). Analyzing Longitudinal Trial
#' Data -- A Practical Guide. Chapman `&amp;` Hall/ CRC Biostatistics Series.
#' @family help
#' @importFrom brms brm brmsformula get_prior prior unstr
#' @importFrom coda as.mcmc
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189 changes: 189 additions & 0 deletions inst/asa.csl
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0 vignettes/bibliography.bib → inst/bibliography.bib
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10 changes: 6 additions & 4 deletions man/brms.mmrm-package.Rd
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