Package: mnlfa 0.4-35

mnlfa: Moderated Nonlinear Factor Analysis

Conducts moderated nonlinear factor analysis (e.g., Curran et al., 2014, <doi:10.1080/00273171.2014.889594>). Regularization methods are implemented for assessing non-invariant items. The package includes undimensional factor models for dichotomous (1PL/2PL), polytomous (GPCM) and continuous (normal distribution) items.

Authors:Alexander Robitzsch [aut, cre]

mnlfa_0.4-35.tar.gz
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mnlfa_0.4-35.tgz(r-4.6-x86_64)mnlfa_0.4-35.tgz(r-4.6-arm64)mnlfa_0.4-35.tgz(r-4.5-x86_64)mnlfa_0.4-35.tgz(r-4.5-arm64)
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mnlfa_0.4-35.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mnlfa/json (API)

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

Bug tracker:https://github.com/alexanderrobitzsch/mnlfa/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

3.30 score 4 stars 193 downloads 2 exports 12 dependencies

Last updated from:b97ba9bff6. Checks:11 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64ERROR157
linux-devel-x86_64ERROR163
source / vignettesOK202
linux-release-arm64ERROR163
linux-release-x86_64ERROR169
macos-release-arm64ERROR167
macos-release-x86_64ERROR277
macos-oldrel-arm64ERROR115
macos-oldrel-x86_64ERROR247
windows-develERROR124
windows-releaseERROR131
windows-oldrelERROR117
wasm-releaseOK144

Exports:mnlfamnlfa_expand_to_list

Dependencies:admiscCDMlatticeMatrixmvtnormpbapplypbvpolycorRcppRcppArmadillosirtTAM