• LISREL

  • Referenced in 336 articles [sw06514]
  • latent (unobservable) variables. If data are collected for the observed variables of the theoretical model...
  • TETRAD

  • Referenced in 430 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 ... random-effects 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 71 articles [sw07227]
  • latent variable models, including confirmatory factor analysis, structural equation modeling and latent growth curve models...
  • GTM

  • Referenced in 57 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 non-linear latent variable model called the Generative Topographic Mapping...
  • ltm

  • Referenced in 42 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 44 articles [sw09312]
  • Bayesian inference for logistic models using Pólya-Gamma latent variables. We propose a new data...
  • ADMB

  • Referenced in 16 articles [sw07416]
  • automatic differentiation, aimed at highly nonlinear models with a large number of parameters. The benefits ... high-dimensional integrals for use in latent variable models. We also review the literature...
  • poLCA

  • Referenced in 25 articles [sw11801]
  • Polytomous Variable Latent Class Analysis. Latent class analysis and latent class regression models for polytomous...
  • bfa

  • Referenced in 25 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...
  • clustMD

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

  • Referenced in 5 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...
  • lavaan.survey

  • Referenced in 6 articles [sw11938]
  • with latent variables and many other latent variable models while correcting estimates, standard errors...
  • Lord-Wingersky

  • 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 lava-package. 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...
  • Attribute2Image

  • Referenced in 5 articles [sw24589]
  • develop a layered generative model with disentangled latent variables that can be learned ... proposed models are capable of generating realistic and diverse samples with disentangled latent representations ... inference of latent variables given novel images. Therefore, the learned generative models show excellent quantitative...