Package: mifa 0.2.1

mifa: Multiple Imputation for Exploratory Factor Analysis

Impute the covariance matrix of incomplete data so that factor analysis can be performed. Imputations are made using multiple imputation by Multivariate Imputation with Chained Equations (MICE) and combined with Rubin's rules. Parametric Fieller confidence intervals and nonparametric bootstrap confidence intervals can be obtained for the variance explained by different numbers of principal components. The method is described in Nassiri et al. (2018) <doi:10.3758/s13428-017-1013-4>.

Authors:Vahid Nassiri [aut], Anikó Lovik [aut], Geert Molenberghs [aut], Geert Verbeke [aut], Tobias Busch [aut, cre]

mifa_0.2.1.tar.gz
mifa_0.2.1.zip(r-4.7-any)mifa_0.2.1.zip(r-4.6-any)mifa_0.2.1.zip(r-4.5-any)
mifa_0.2.1.tgz(r-4.6-any)mifa_0.2.1.tgz(r-4.5-any)
mifa_0.2.1.tar.gz(r-4.7-any)mifa_0.2.1.tar.gz(r-4.6-any)
mifa_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mifa/json (API)

# Install 'mifa' in R:
install.packages('mifa', repos = c('https://teebusch.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/teebusch/mifa/issues

On CRAN:

Conda:

factor-analysisimputation

3.00 score 2 stars 5 scripts 297 downloads 3 exports 63 dependencies

Last updated from:8c87981278. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK155
source / vignettesOK177
linux-releaseOK146
macos-releaseOK191
macos-oldrelOK168
windows-develOK97
windows-releaseOK94
windows-oldrelOK77
wasm-releaseOK113

Exports:mifamifa_ci_bootmifa_ci_fieller

Dependencies:backportsbitbit64bootbroomcheckmateclicliprcodetoolscpp11crayondplyrforcatsforeachgenericsglmnetgluehavenhmsiteratorsjomolatticelifecyclelme4magrittrMASSMatrixmiceminqamitmlnlmenloptrnnetnumDerivordinalpanpillarpkgconfigprettyunitsprogresspurrrR6rbibutilsRcppRcppEigenRdpackreadrreformulasrlangrpartshapestringistringrsurvivaltibbletidyrtidyselecttzdbucminfutf8vctrsvroomwithr