mantar: Missingness Alleviation for Network Analysis
Provides functionality for estimating cross-sectional network structures representing partial correlations in R, while accounting for missing values in the data. Networks are estimated via neighborhood selection, i.e., node-wise multiple regression, with model selection guided by information criteria. Missing data can be handled primarily via multiple imputation or a maximum likelihood-based approach; deletion techniques are available but secondary <doi:10.31234/osf.io/qpj35>.
Version: |
0.1.0 |
Depends: |
R (≥ 4.1.0) |
Imports: |
stats |
Suggests: |
mice, lavaan, qgraph, testthat (≥ 3.0.0) |
Published: |
2025-07-11 |
Author: |
Kai Jannik Nehler
[aut, cre] |
Maintainer: |
Kai Jannik Nehler <nehler at psych.uni-frankfurt.de> |
License: |
GPL (≥ 3) |
NeedsCompilation: |
no |
Materials: |
README |
CRAN checks: |
mantar results |
Documentation:
Downloads:
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