Showing 3 of total 3 results (show query)
yrosseel
lavaan:Latent Variable Analysis
Fit a variety of latent variable models, including confirmatory factor analysis, structural equation modeling and latent growth curve models.
Maintained by Yves Rosseel. Last updated 22 hours ago.
factor-analysisgrowth-curve-modelslatent-variablesmissing-datamultilevel-modelsmultivariate-analysispath-analysispsychometricsstatistical-modelingstructural-equation-modeling
455 stars 16.81 score 8.4k scripts 217 dependents
ecmerkle
blavaan:Bayesian Latent Variable Analysis
Fit a variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve models. References: Merkle & Rosseel (2018) <doi:10.18637/jss.v085.i04>; Merkle et al. (2021) <doi:10.18637/jss.v100.i06>.
Maintained by Edgar Merkle. Last updated 14 days ago.
bayesian-statisticsfactor-analysisgrowth-curve-modelslatent-variablesmissing-datamultilevel-modelsmultivariate-analysispath-analysispsychometricsstatistical-modelingstructural-equation-modelingcpp
92 stars 10.84 score 183 scripts 3 dependents
egeminiani
penfa:Single- And Multiple-Group Penalized Factor Analysis
Fits single- and multiple-group penalized factor analysis models via a trust-region algorithm with integrated automatic multiple tuning parameter selection (Geminiani et al., 2021 <doi:10.1007/s11336-021-09751-8>). Available penalties include lasso, adaptive lasso, scad, mcp, and ridge.
Maintained by Elena Geminiani. Last updated 4 years ago.
factor-analysislassolatent-variablesmultiple-groupoptimizationpenalizationpsychometrics
3 stars 4.48 score 5 scripts