c(person("Emmanuel", "Paradis", role = c("aut", "cre", "cph"), email = "Emmanuel.Paradis@ird.fr"),
person("Klaus", "Schliep", role = "aut"),
person("Alastair", "Potts", role = "aut"))
Emmanuel Paradis [aut, cre, cph],
Klaus Schliep [aut],
Alastair Potts [aut]

c(person("Emmanuel", "Paradis", role = c("aut", "cre", "cph"), email = "Emmanuel.Paradis@ird.fr", comment = c(ORCID = "0000-0003-3092-2199")),
person("Thibaut", "Jombart", role = c("aut", "cph"), comment = c(ORCID = "0000-0003-2226-8692")),
person("Zhian N.", "Kamvar", role = c("aut", "cph"), comment = c(ORCID = "0000-0003-1458-7108")),
person("Brian", "Knaus", role = c("aut", "cph"), comment = c(ORCID = "0000-0003-1665-4343")),
person("Klaus", "Schliep", role = c("aut", "cph"), comment = c(ORCID = "0000-0003-2941-0161")),
person("Alastair", "Potts", role = c("aut", "cph"), comment = c(ORCID = "0000-0003-0919-7279")),
person("David", "Winter", role = c("aut", "cph"), comment = c(ORCID = "0000-0002-6165-0029")))

Data About Historic Pell Grant Distribution in the US
person("Arafath", "Hossain", , "a.h.fahad90@gmail.com", role = c("aut", "cre"))
Historic Pell grant data as provided by the US Department of Education.
This package contains data about how much pell grant was awarded by which institution in
which year.
This data comes from the US Department of Education. Raw data can be downloaded from here: <https://www2.ed.gov/finaid/prof/resources/data/pell-institution.html>.
dplyr, knitr, rmarkdown, treemap, visdat

c(
person(c("Caspar", "J"),
"van Lissa",
role = c("aut", "cre"),
email = "c.j.vanlissa@uu.nl",
comment = c(ORCID = "0000-0002-0808-5024")),
person(c("Sara", "J"), "van Erp", role = c("aut"))
)
Conduct penalized meta-analysis, see Van Lissa & Van Erp (2021).
<doi:10.31234/osf.io/6phs5>. In meta-analysis, there are
often between-study differences. These can be coded as moderator variables,
and controlled for using meta-regression. However, if the number of
moderators is large relative to the number of studies, such an analysis may
be overfit. Penalized meta-regression is useful in these cases, because
it shrinks the regression slopes of irrelevant moderators towards zero.
methods, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rstantools
(>= 2.1.1), sn
Caspar J van Lissa [aut, cre] (<https://orcid.org/0000-0002-0808-5024>),
Sara J van Erp [aut]