
LISREL
 Referenced in 339 articles
[sw06514]
 latent (unobservable) variables. If data are collected for the observed variables of the theoretical model...

TETRAD
 Referenced in 441 articles
[sw12177]
 unobserved confounders of measured variables, to search for models of latent structure, and to search...

Latent GOLD
 Referenced in 94 articles
[sw11673]
 variable X. Since the latent variable is categorical, LC modeling differs from more traditional latent ... randomeffects regression models that are based on continuous latent variables. Latent class (LC) analysis ... methodology was formalized and extended to nominal variables by Goodman (1974a, 1974b) who also developed ... Latent GOLD program. Over the same period, the related field of finite mixture (FM) models...

lavaan
 Referenced in 72 articles
[sw07227]
 latent variable models, including confirmatory factor analysis, structural equation modeling and latent growth curve models...

GTM
 Referenced in 58 articles
[sw39434]
 Generative Topographic Mapping. Latent variable models represent the probability density of data in a space ... smaller number of latent, or hidden, variables. A familiar example is factor analysis which ... introduce a form of nonlinear latent variable model called the Generative Topographic Mapping...

ltm
 Referenced in 45 articles
[sw07911]
 package for latent variable modelling and item response theory analyses. The R package ... multivariate dichotomous and polytomous data using latent variable models, under the Item Response Theory approach...

BayesLogit
 Referenced in 46 articles
[sw09312]
 Bayesian inference for logistic models using PólyaGamma latent variables. We propose a new data...

ADMB
 Referenced in 17 articles
[sw07416]
 automatic differentiation, aimed at highly nonlinear models with a large number of parameters. The benefits ... highdimensional integrals for use in latent variable models. We also review the literature...

bfa
 Referenced in 28 articles
[sw07430]
 factor models for mixed data. Gaussian factor models have proven widely useful for parsimoniously characterizing ... variables, using latent Gaussian variables or through generalized latent trait models accommodating measurements ... Gaussian measured variables, the latent variables typically influence both the dependence structure and the form ... Bayesian Gaussian copula factor models that decouple the latent factors from the marginal distributions...

poLCA
 Referenced in 26 articles
[sw11801]
 Polytomous Variable Latent Class Analysis. Latent class analysis and latent class regression models for polytomous...

MplusAutomation
 Referenced in 6 articles
[sw11281]
 MplusAutomation: Automating Mplus Model Estimation and Interpretation. The MplusAutomation package leverages the flexibility ... language to automate latent variable model estimation and interpretation using Mplus, a powerful latent variable...

clustMD
 Referenced in 13 articles
[sw25059]
 clustMD: Model Based Clustering for Mixed Data. Modelbased clustering of mixed data (i.e. data ... using a parsimonious mixture of latent Gaussian variable models...

lavaan.survey
 Referenced in 6 articles
[sw11938]
 with latent variables and many other latent variable models while correcting estimates, standard errors...

LordWingersky
 Referenced in 13 articles
[sw41250]
 purposes, for example, scoring, scale alignment, and model fit checking. In the research reported here ... summed score likelihoods for all latent variables in the model conditional on observed score combinations...

PixelVAE
 Referenced in 4 articles
[sw36214]
 PixelVAE: A Latent Variable Model for Natural Images. Natural image modeling is a landmark challenge ... learning. Variational Autoencoders (VAEs) learn a useful latent representation and model global structure well ... Finally, we extend our model to a hierarchy of latent variables at different scales...

PROC CALIS
 Referenced in 5 articles
[sw12071]
 Overview: CALIS Procedure: Structural equation modeling is an important statistical tool in social and behavioral ... variables that can be either observed variables (manifest variables) or unobserved hypothetical variables (latent variables ... introduction to latent variable models, see Loehlin (2004), Bollen (1989b), Everitt (1984), or Long...

lava
 Referenced in 3 articles
[sw11263]
 Linear latent variable models: the lavapackage. An R package for specifying and estimating linear ... latent variable models is presented. The philosophy of the implementation is to separate the model...

blavaan
 Referenced in 4 articles
[sw24888]
 Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve...

lvnet
 Referenced in 4 articles
[sw19428]
 Variable Network Modeling. Estimate, fit and compare Structural Equation Models (SEM) and network models (Gaussian ... Graphical Models; GGM) using OpenMx. Allows for two possible generalizations to include GGMs ... used between latent variables (latent network modeling; LNM) or between residuals (residual network modeling...

psychonetrics
 Referenced in 3 articles
[sw34796]
 timeseries data. This assumes that all variables are measured without measurement error, which ... general framework that extends GGM modeling with latent variables, including relationships over time. These relationships ... least three waves of measurement. The model takes the form ... graphical vectorautoregression model between latent variables and is termed the extit{tslvgvar} when...