English, Article edition: GLLAMM: Stata program to fit generalised linear latent and mixed models Sophia Rabe-Hesketh

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  • code
Language
  • English

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Title
  • GLLAMM: Stata program to fit generalised linear latent and mixed models
Author
  • Sophia Rabe-Hesketh
Physical Description
  • code
Notes
  • gllamm fits generalized linear latent and mixed models. These models include Multilevel generalized linear regression models (extensions of the simple random intercept models that may be fitted in Stata using xtreg, xtlogit, xtpois to include multilevel and random coefficient models), Multilevel factor models and Multilevel structural equation models. The latent variables (or random effects) can be assumed to have a multivariate normal distribution or to be discrete allowing nonparametric maximum likelihood estimation. The common links and families of generalized linear models are available and responses can be of mixed type including continuous, censored, discrete, dichotomous, ordered categorical and unordered categorical. The version of gllamm (gllamm6) described in STB-53, (sg129, p47-57) does not incorporate many of the features outlined above. This is version 2.3.13 of the software (Nov 2006). A manual in PDF form is available from the SSC archive via web browser.
  • multilevel models, mixed models, random coefficients, latent variable models, gllamm6, gllamm, structural equation models, factor models, mixed responses
  • RePEc:boc:bocode:s401701
Language
  • English
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