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)mifa_0.2.1.zip(r-4.6)mifa_0.2.1.zip(r-4.5)
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✨
card.svg |card.png
mifa/json (API)
NEWS

# 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 236 downloads 3 exports 63 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64OK156
source / vignettesOK192
linux-release-x86_64OK192
macos-release-arm64OK151
macos-oldrel-arm64OK194
windows-develOK102
windows-releaseOK86
windows-oldrelOK98
wasm-releaseOK126

Exports:mifamifa_ci_bootmifa_ci_fieller

Dependencies:backportsbitbit64bootbroomcheckmateclicliprcodetoolscpp11crayondplyrforcatsforeachgenericsglmnetgluehavenhmsiteratorsjomolatticelifecyclelme4magrittrMASSMatrixmiceminqamitmlnlmenloptrnnetnumDerivordinalpanpillarpkgconfigprettyunitsprogresspurrrR6rbibutilsRcppRcppEigenRdpackreadrreformulasrlangrpartshapestringistringrsurvivaltibbletidyrtidyselecttzdbucminfutf8vctrsvroomwithr