bayestestR, boot, brms, data.table, dplyr, effectsize, gamm4,
ggplot2, haven, htmltools, httr, knitr, lme4, mediation,
parameters, poorman (>= 0.2.6), psych, readxl, readr, rio,
rmarkdown, rstanarm, see, testthat (>= 3.1.0), tidyr, withr

A lightweight package to assist in key steps involved in any data
analysis workflow: (1) wrangling the raw data to get it in the needed form,
(2) applying preprocessing steps and statistical transformations, and
(3) compute statistical summaries of data properties and distributions.
It is also the data wrangling backend for packages in 'easystats' ecosystem.
bayestestR, boot, brms, data.table, dplyr (>= 1.0),
effectsize, gamm4, ggplot2, haven, htmltools, httr, knitr,
lme4, mediation, parameters, poorman (>= 0.2.6), psych, readxl,
readr, rio, rmarkdown, rstanarm, see, testthat (>= 3.1.0),
tidyr, withr

c(
person("Indrajeet", "Patil", , "patilindrajeet.science@gmail.com", role = c("aut", "cre"),
comment = c(ORCID = "0000-0003-1995-6531", Twitter = "@patilindrajeets")),
person("Dominique", "Makowski", , "dom.makowski@gmail.com", role = "aut",
comment = c(ORCID = "0000-0001-5375-9967", Twitter = "@Dom_Makowski")),
person("Daniel", "Lüdecke", , "d.luedecke@uke.de", role = "aut",
comment = c(ORCID = "0000-0002-8895-3206", Twitter = "@strengejacke")),
person("Mattan S.", "Ben-Shachar", , "matanshm@post.bgu.ac.il", role = "aut",
comment = c(ORCID = "0000-0002-4287-4801")),
person("Brenton M.", "Wiernik", , "brenton@wiernik.org", role = "aut",
comment = c(ORCID = "0000-0001-9560-6336", Twitter = "@bmwiernik")),
person("Etienne", "Bacher", , "etienne.bacher@protonmail.com", role = "aut",
comment = c(ORCID = "0000-0002-9271-5075")),
person("Rémi", "Thériault", , "remi.theriault@mail.mcgill.ca", role = "ctb",
comment = c(ORCID = "0000-0003-4315-6788", Twitter = "@rempsyc")),
person("Thomas J.", "Faulkenberry", , "faulkenberry@tarleton.edu", role = "rev"),
person("Robert", "Garrett", , "rcg4@illinois.edu", role = "rev")
)
A lightweight package to assist in key steps involved in any data
analysis workflow: (1) wrangling the raw data to get it in the needed form,
(2) applying preprocessing steps and statistical transformations, and
(3) compute statistical summaries of data properties and distributions.
It is also the data wrangling backend for packages in 'easystats' ecosystem.
References: Patil et al. (2022) <doi:10.21105/joss.04684>.
Indrajeet Patil [aut, cre] (<https://orcid.org/0000-0003-1995-6531>,
@patilindrajeets),
Dominique Makowski [aut] (<https://orcid.org/0000-0001-5375-9967>,
@Dom_Makowski),
Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>,
@strengejacke),
Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>),
Brenton M. Wiernik [aut] (<https://orcid.org/0000-0001-9560-6336>,
@bmwiernik),
Etienne Bacher [aut] (<https://orcid.org/0000-0002-9271-5075>),
Rémi Thériault [ctb] (<https://orcid.org/0000-0003-4315-6788>,
@rempsyc),
Thomas J. Faulkenberry [rev],
Robert Garrett [rev]