Package: mifa 0.2.0

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_0.2.0.tar.gz
mifa_0.2.0.zip(r-4.5)mifa_0.2.0.zip(r-4.4)mifa_0.2.0.zip(r-4.3)
mifa_0.2.0.tgz(r-4.4-any)mifa_0.2.0.tgz(r-4.3-any)
mifa_0.2.0.tar.gz(r-4.5-noble)mifa_0.2.0.tar.gz(r-4.4-noble)
mifa_0.2.0.tgz(r-4.4-emscripten)mifa_0.2.0.tgz(r-4.3-emscripten)
mifa.pdf |mifa.html
mifa/json (API)
NEWS

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

Peer review:

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

On CRAN:

factor-analysisimputation

3.00 score 2 stars 5 scripts 140 downloads 3 exports 61 dependencies

Last updated 4 years agofrom:b789c31398. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 08 2024
R-4.5-winNOTENov 08 2024
R-4.5-linuxNOTENov 08 2024
R-4.4-winOKNov 08 2024
R-4.4-macOKNov 08 2024
R-4.3-winOKNov 08 2024
R-4.3-macOKNov 08 2024

Exports:mifamifa_ci_bootmifa_ci_fieller

Dependencies:backportsbitbit64bootbroomcheckmateclicliprcodetoolscpp11crayondplyrfansiforcatsforeachgenericsglmnetgluehavenhmsiteratorsjomolatticelifecyclelme4magrittrMASSMatrixmiceminqamitmlnlmenloptrnnetnumDerivordinalpanpillarpkgconfigprettyunitsprogresspurrrR6RcppRcppEigenreadrrlangrpartshapestringistringrsurvivaltibbletidyrtidyselecttzdbucminfutf8vctrsvroomwithr