accdata, covr, knitr, rmarkdown, testthat (>= 3.0.0)

Imprecise Imputation for Statistical Matching
c(person("Paul", "Fink",
email = "paul.fink@stat.uni-muenchen.de",
role = c("aut", "cre")),
person("Eva", "Endres",
email = "eva.endres@stat.uni-muenchen.de",
role = c("aut")),
person("Melissa", "Schmoll",
email = "",
role = c("ctb")))
Imputing blockwise missing data by imprecise imputation,
featuring a domain-based, variable-wise, and case-wise strategy.
Furthermore, the estimation of lower and upper bounds for
unconditional and conditional probabilities based on the obtained
imprecise data is implemented.
Additionally, two utility functions are supplied: one to check
whether variables in a data set contain set-valued observations;
and another to merge two already imprecisely imputed data.
Paul Fink [aut, cre],
Eva Endres [aut],
Melissa Schmoll [ctb]

Imputing blockwise missing data by imprecise imputation,
featuring a domain-based, variable-wise, and case-wise strategy.
Furthermore, the estimation of lower and upper bounds for
unconditional and conditional probabilities based on the obtained
imprecise data is implemented.
Additionally, two utility functions are supplied: one to check
whether variables in a data set contain set-valued observations;
and another to merge two already imprecisely imputed data.
The method is described in a technical report by Endres, Fink and
Augustin (2018, <doi:10.5282/ubm/epub.42423>).

Array Operations for Arrays of Mismatching Sizes
Support for implicit expansion of arrays in operations involving
arrays of mismatching sizes. This pattern is known as "broadcasting" in
'Python' and  "implicit expansion" in 'Matlab' and is explained for example in
the article "Array programming with NumPy" by C. R. Harris et al. (2020)
<doi:10.1038/s41586-020-2649-2>.
c(person(
given = "Manuel",
family = "Hentschel",
role = c("aut", "cre"),
email = "Manuel.Hentschel@unige.ch"
))

Computes the Scores for Different Implicit Measures
Ottavia M. Epifania [aut, cre],
Pasquale Anselmi [ctb],
Egidio Robusto [ctb]
A tool for computing the scores for the Implicit Association Test
(IAT; Greenwald, McGhee & Schwartz (1998) <doi:10.1037/0022-3514.74.6.1464>)
and the Single Category-IAT (SC-IAT: Karpinski & Steinman
(2006) <doi:10.1037/0022-3514.91.1.16>). Functions for preparing the data
(both for the IAT and the SC-IAT), plotting the results, and obtaining a
table with the scores of implicit measures descriptive statistics are
provided.
dplyr, ggplot2, methods, plyr, qpdf, tidyr, xtable
testthat (>= 2.1.0), knitr, rmarkdown, tableHTML, data.table