lavaan: An R package for structural equation modeling. Fit a variety of latent variable models, including confirmatory factor analysis, structural equation modeling and latent growth curve models.

References in zbMATH (referenced in 59 articles , 1 standard article )

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  1. Fernando Palluzzi, Mario Grassi: SEMgraph: An R Package for Causal Network Analysis of High-Throughput Data with Structural Equation Models (2021) arXiv
  2. Boudt, Kris; Cornilly, Dries; Verdonck, Tim: Nearest comoment estimation with unobserved factors (2020)
  3. Calcagnì, Antonio; Lombardi, Luigi; Avanzi, Lorenzo; Pascali, Eduardo: Multiple mediation analysis for interval-valued data (2020)
  4. Fisher, Zachary F.; Bollen, Kenneth A.: An instrumental variable estimator for mixed indicators: analytic derivatives and alternative parameterizations (2020)
  5. Jorgensen, Terrence D.; Jak, Suzanne: Book review of: K. Gana and G. Broc, Structural equation modeling with lavaan (2020)
  6. Markus D. Steiner; Silvia Grieder: EFAtools: An R package with fast and exible implementations of exploratory factor analysis tools (2020) not zbMATH
  7. Panagiotis Papastamoulis, Ioannis Ntzoufras: On the identifiability of Bayesian factor analytic models (2020) arXiv
  8. Po-Hsien Huang: lslx: Semi-Confirmatory Structural Equation Modeling via Penalized Likelihood (2020) not zbMATH
  9. Rockwood, Nicholas J.: Maximum likelihood estimation of multilevel structural equation models with random slopes for latent covariates (2020)
  10. Cui, Ruifei; Bucur, Ioan Gabriel; Groot, Perry; Heskes, Tom: A novel Bayesian approach for latent variable modeling from mixed data with missing values (2019)
  11. Drton, Mathias; Fox, Christopher; Wang, Y. Samuel: Computation of maximum likelihood estimates in cyclic structural equation models (2019)
  12. Foldnes, Njål; Grønneberg, Steffen: On identification and non-normal simulation in ordinal covariance and item response models (2019)
  13. Gana, Kamel; Broc, Guillaume: Structural equation modeling with lavaan (2019)
  14. Grønneberg, Steffen; Foldnes, Njål: A problem with discretizing Vale-Maurelli in simulation studies (2019)
  15. Hong, Maxwell R.; Jacobucci, Ross: Book review of: K. J. Grimm et al., Growth modeling. Structural equation and multilevel modeling approaches (2019)
  16. Lai, Keke: Creating misspecified models in moment structure analysis (2019)
  17. Merkle, Edgar C.; Furr, Daniel; Rabe-Hesketh, Sophia: Bayesian comparison of latent variable models: conditional versus marginal likelihoods (2019)
  18. Meshcheryakov Georgy, Igolkina Anna: semopy: A Python package for Structural Equation Modeling (2019) arXiv
  19. Papageorgiou, Ioulia; Moustaki, Irini: Sampling of pairs in pairwise likelihood estimation for latent variable models with categorical observed variables (2019)
  20. Paul-Christian Burkner: thurstonianIRT: Thurstonian IRT Models in R (2019) not zbMATH

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