Latent Variable Forests for Latent Variable Score Estimation. [PDF]
Educ Psychol MeasWe develop a latent variable forest (LV Forest) algorithm for the estimation of latent variable scores with one or more latent variables. LV Forest estimates unbiased latent variable scores based on confirmatory factor analysis (CFA) models with ordinal and/or numerical response variables.
Classe F, Kern C.
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Testing and Interpreting Latent Variable Interactions Using the semTools Package
Psych, 2021 Examining interactions among predictors is an important part of a developing research program. Estimating interactions using latent variables provides additional power to detect effects over testing interactions in regression.
Alexander M. Schoemann +1 more
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Inference after latent variable estimation for single-cell RNA sequencing data. [PDF]
Biostatistics, 2023 In the analysis of single-cell RNA sequencing data, researchers often characterize the variation between cells by estimating a latent variable, such as cell type or pseudotime, representing some aspect of the cell's state.
Neufeld A +4 more
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Family resilience, emotional intelligence, and non-suicidal self-injury among Chinese adolescents with mental disorders: a latent variable mediation analysis [PDF]
Frontiers in PsychiatryBackgroundNon-suicidal self-injury (NSSI) is a common malpractice in adolescents with mental disorders. It may lead to suicide or other adverse consequences, thus affecting the treatment and rehabilitation of patients. We herein analyzed the relationship
Zhengmin Zhu +5 more
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Proportion Explained Component Variance in Second-Order Scales: A Note on a Latent Variable Modeling Approach. [PDF]
Educ Psychol MeasRaykov T, DiStefano C, Ransome Y.
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Posterior Collapse and Latent Variable Non-identifiability [PDF]
Neural Information Processing Systems, 2023 Variational autoencoders model high-dimensional data by positing low-dimensional latent variables that are mapped through a flexible distribution parametrized by a neural network.
Yixin Wang, D. Blei, J. Cunningham
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GFlowNet-EM for learning compositional latent variable models [PDF]
International Conference on Machine Learning, 2023 Latent variable models (LVMs) with discrete compositional latents are an important but challenging setting due to a combinatorially large number of possible configurations of the latents.
Edward J. Hu +5 more
semanticscholar +1 more source
Data Analysis with SPSS for Survey-based Research, 2004 Vermunt, J.K., Magidson, J.
semanticscholar +5 more sources
Multi-Scale Multi-Kernel Gaussian Process Latent Variable Model [PDF]
Jisuanji gongcheng, 2021 As an unsupervised Bayesian non-parameter dimension reduction model,the Gaussian Process Latent Variable Model(GPLVM) fails to efficiently utilize semantic label information of data.Moreover,it just assumes that the features of all observed variables are
ZHOU Peichun, WU Lan'an
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Gaussian process latent variable models-ANN based method for automatic features selection and dimensionality reduction for control of EMG-driven systems. [PDF]
Front Artif IntellNayab M +6 more
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