c(
person("Gannaz", "Irene", email = "irene.gannaz@insa-lyon.fr", role = c("aut","cre")),
person("Roux", "Marine", email = "marine.roux@gipsa-lab.fr", role = "aut"))
Gannaz Irene [aut, cre],
Roux Marine [aut]

c(
person("Gannaz", "Irene", email = "irene.gannaz@insa-lyon.fr", role = c("aut","cre")))

Missing Item Responses Imputation for Test and Assessment Data
c(person("Shenghai", "Dai", role = c("aut", "cre"),
email = "dais@indiana.edu"),
person("Xiaolin", "Wang", role = "aut"),
person("Dubravka", "Svetina", role = "aut"))
Shenghai Dai [aut, cre],
Xiaolin Wang [aut],
Dubravka Svetina [aut]
Functions for imputing missing item responses for dichotomous and
polytomous test and assessment data. This package enables missing imputation
methods that are suitable for test and assessment data, including: listwise (LW)
deletion, treating as incorrect (IN), person mean imputation (PM), item mean
imputation (IM), two-way imputation (TW), logistic regression imputation (LR),
and EM imputation.

c(person("Shenghai", "Dai", role = c("aut", "cre"),
email = "s.dai@wsu.edu"),
person("Xiaolin", "Wang", role = "aut"),
person("Dubravka", "Svetina", role = "aut"))

Functions for imputing missing item responses for dichotomous and
polytomous test and assessment data. This package enables missing imputation
methods that are suitable for test and assessment data, including:
listwise (LW) deletion (see De Ayala et al. 2001 <doi:10.1111/j.1745-3984.2001.tb01124.x>),
treating as incorrect (IN, see Lord, 1974 <doi: 10.1111/j.1745-3984.1974.tb00996.x>;
Mislevy & Wu, 1996 <doi: 10.1002/j.2333-8504.1996.tb01708.x>;
Pohl et al., 2014 <doi: 10.1177/0013164413504926>), person mean imputation (PM), item mean
imputation (IM), two-way imputation (TW, see Sijtsma & van der Ark, 2003 <doi: 10.1207/s15327906mbr3804_4>),
logistic regression imputation (LR), and expectation–maximization (EM)
imputation (see Finch, 2008 <doi: 10.1111/j.1745-3984.2008.00062.x>).

Functions for imputing missing item responses for dichotomous and
polytomous test and assessment data. This package enables missing imputation
methods that are suitable for test and assessment data, including:
listwise (LW) deletion (see De Ayala et al. 2001 <doi:10.1111/j.1745-3984.2001.tb01124.x>),
treating as incorrect (IN, see Lord, 1974 <doi: 10.1111/j.1745-3984.1974.tb00996.x>;
Mislevy & Wu, 1996 <doi: 10.1002/j.2333-8504.1996.tb01708.x>;
Pohl et al., 2014 <doi: 10.1177/0013164413504926>), person mean imputation (PM),
item mean imputation (IM), two-way (TW) and response function (RF) imputation
(see Sijtsma & van der Ark, 2003 <doi: 10.1207/s15327906mbr3804_4>),
logistic regression (LR) imputation, and expectation–maximization (EM)
imputation (see Finch, 2008 <doi: 10.1111/j.1745-3984.2008.00062.x>).