Multiple Imputation for Exploratory Factor Analysis
Overview
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.
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Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK13 OK2026-05-02
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- ERROR11 OK, 1 ERROR2026-04-25
- OK14 OK2026-03-10
Documentation
- Help pages
- 9 (6 internal)
- Examples that run
- 0%3 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 44%
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- not measured
- Median days to close, 50 most recently updated closed PRs
- 0
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9 development-tooling and community-health practices detected across 5 families in the upstream repository
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Dependencies
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- RR 4.6.0 released · 2026-04-24
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- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 0.2.02021-01-22
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2021-01-22
- Total releases
- 2 / 5 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 137 KB
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