IDEAS home Printed from https://ideas.repec.org/p/boc/usug01/16.html
   My bibliography  Save this paper

Extensions to gllamm6

Author

Listed:
  • Sophia Rabe-Hesketh

    () (Institute of Psychiatry)

  • Andrew Pickles

    (University of Manchester)

  • Anders Skrondal

    (National Institute of Public Health, Oslo)

Abstract

gllamm is a program to fit generalised linear latent and mixed models. Since gllamm6 appeared in the STB (sg129), a large number of new features have been added. Two important extensions will be discussed: 1) More response processes can now be modelled including ordered and unordered categorical responses and rankings. Multilevel models for nominal data and rankings will be described and fitted in gllamm. 2) Multilevel structural equation models can be fitted by specifying regressions of latent variables on other latent variables and on explanatory variables. Examples will be described and fitted in gllamm. Other new features in gllamm include parameter constraints, and a 'post-estimation' program, gllapred, for estimating posterior means and probabilities.

Suggested Citation

  • Sophia Rabe-Hesketh & Andrew Pickles & Anders Skrondal, 2001. "Extensions to gllamm6," United Kingdom Stata Users' Group Meetings 2001 16, Stata Users Group.
  • Handle: RePEc:boc:usug01:16
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/RePEc/usug2001/ukgllamm.pdf
    Download Restriction: no

    File URL: http://fmwww.bc.edu/RePEc/usug2001/ukgllamm.ps
    Download Restriction: no

    File URL: http://www.iop.kcl.ac.uk/IoP/Departments/BioComp/programs/gllamm.html
    File Function: program description
    Download Restriction: no

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:boc:usug01:16. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F Baum). General contact details of provider: http://edirc.repec.org/data/stataea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.