- Referenced in 339 articles
- theoretical models for observed and latent (unobservable) variables. If data are collected for the observed...
- Referenced in 94 articles
- distinct categories of a nominal latent variable X. Since the latent variable is categorical ... modeling differs from more traditional latent variable approaches such as factor analysis, structural equation models ... models that are based on continuous latent variables. Latent class (LC) analysis was originally introduced ... methodology was formalized and extended to nominal variables by Goodman (1974a, 1974b) who also developed...
- Referenced in 441 articles
- unobserved confounders of measured variables, to search for models of latent structure, and to search...
- Referenced in 92 articles
- CPDAG can be estimated if latent variables and/or selection variables are assumed to be present...
- Referenced in 58 articles
- 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 ... based on a linear transformations between the latent space and the data space. In this ... introduce a form of non-linear latent variable model called the Generative Topographic Mapping...
- Referenced in 72 articles
- equation modeling. Fit a variety of latent variable models, including confirmatory factor analysis, structural equation...
- Referenced in 45 articles
- 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...
- Referenced in 46 articles
- logistic models using Pólya-Gamma latent variables. We propose a new data-augmentation strategy...
- Referenced in 28 articles
- extension to mixed categorical and continuous variables, using latent Gaussian variables or through generalized latent ... Gaussian measured variables, the latent variables typically influence both the dependence structure and the form ... Gaussian copula factor models that decouple the latent factors from the marginal distributions. A semiparametric...
- Referenced in 26 articles
- package poLCA: Polytomous Variable Latent Class Analysis. Latent class analysis and latent class regression models ... polytomous outcome variables. Also known as latent structure analysis...
- Referenced in 27 articles
- between a small subset of the latent variables and the observation. We derive a lower...
- Referenced in 20 articles
- exact log-likelihood, tractability of exact latent-variable inference, and parallelizability of both training...
- Referenced in 18 articles
- factorized distribution, i.e., resulting in independent latent variables. We parametrize this transformation so that computing...
- Referenced in 17 articles
- high-dimensional integrals for use in latent variable models. We also review the literature...
- Referenced in 13 articles
- summed score likelihoods for all latent variables in the model conditional on observed score combinations...
- Referenced in 11 articles
- applied to counter the effects of latent variables on the rankings of hypotheses. The estimation...
- Referenced in 10 articles
- that specifies and encapsulates primitive random variables. The SPI supports custom control flow, higher-order ... external models that do inference over latent variables hidden from Venture. Second, we describe probabilistic...
- Referenced in 13 articles
- variables) using a parsimonious mixture of latent Gaussian variable models...
- Referenced in 6 articles
- factor analysis, multivariate regression models with latent variables and many other latent variable models while...
- Referenced in 9 articles
- cases and 100 observed variables. GeSCA currently enables users to: use Microsoft® Excel ... three different procedures. handle second-order latent variables in single-group analyses...