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.
- Version0.2.0
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- Last release01/22/2021
Documentation
Team
Tobias Busch
Vahid Nassiri
Show author detailsRolesAuthorGeert Molenberghs
Show author detailsRolesAuthorGeert Verbeke
Show author detailsRolesAuthorAnikó Lovik
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 185 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 4 times.
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Last 365 days
This package has been downloaded 1,936 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Mar 03, 2025 with 26 downloads.
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Dependencies
- Imports3 packages
- Suggests7 packages