# ------------------------------------------------
# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "lava" in publications use:'
type: software
license: Apache-2.0
title: 'lava: Latent Variable Models'
version: 1.9.2
doi: 10.1007/s00180-012-0344-y
identifiers:
- type: doi
  value: 10.32614/CRAN.package.lava
abstract: A general implementation of Structural Equation Models with latent variables
  (MLE, 2SLS, and composite likelihood estimators) with both continuous, censored,
  and ordinal outcomes (Holst and Budtz-Joergensen (2013) <https://doi.org/10.1007/s00180-012-0344-y>).
  Mixture latent variable models and non-linear latent variable models (Holst and
  Budtz-Joergensen (2020) <https://doi.org/10.1093/biostatistics/kxy082>). The package
  also provides methods for graph exploration (d-separation, back-door criterion),
  simulation of general non-linear latent variable models, and estimation of influence
  functions for a broad range of statistical models.
authors:
- family-names: Holst
  given-names: Klaus K.
  email: klaus@holst.it
preferred-citation:
  type: article
  title: 'Linear Latent Variable Models: The lava-package'
  authors:
  - family-names: Holst
    given-names: Klaus K.
    email: klaus@holst.it
  - family-names: Budtz-Joergensen
    given-names: Esben
  year: '2013'
  volume: '28'
  issue: '4'
  journal: Computational Statistics
  doi: 10.1007/s00180-012-0344-y
  start: 1385-1452
repository: https://cran.r-universe.dev
repository-code: https://github.com/kkholst/lava
commit: fc2d0ad67c2f40a861ef9c531d53dfd77235a4a2
url: https://kkholst.github.io/lava/
date-released: '2026-06-30'
contact:
- family-names: Holst
  given-names: Klaus K.
  email: klaus@holst.it
references:
- type: article
  title: A two-stage estimation procedure for non-linear structural equation models
  authors:
  - family-names: Holst
    given-names: Klaus K.
  - family-names: Budtz-Joergensen
    given-names: Esben
  year: '2020'
  volume: '21'
  issue: '4'
  journal: Biostatistics
  doi: 10.1093/biostatistics/kxy082
  start: 676-691