IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v55y1999i3p839-845.html
   My bibliography  Save this article

Estimating Equations for a Latent Transit ion Model with Multiple Discrete Indicators

Author

Listed:
  • Beth A. Reboussin
  • Kung-Yee Liang
  • David M. Reboussin

Abstract

No abstract is available for this item.

Suggested Citation

  • Beth A. Reboussin & Kung-Yee Liang & David M. Reboussin, 1999. "Estimating Equations for a Latent Transit ion Model with Multiple Discrete Indicators," Biometrics, The International Biometric Society, vol. 55(3), pages 839-845, September.
  • Handle: RePEc:bla:biomet:v:55:y:1999:i:3:p:839-845
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.0006-341X.1999.00839.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Greiner, P.A. & Snowdon, D.A. & Schmitt, F.A., 1996. "The loss of independence in activities of daily living: The role of low normal cognitive function in elderly nuns," American Journal of Public Health, American Public Health Association, vol. 86(1), pages 62-66.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Beth A. Reboussin & Edward H. Ip & Mark Wolfson, 2008. "Locally dependent latent class models with covariates: an application to underā€age drinking in the USA," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(4), pages 877-897, October.
    2. Wall, Melanie M. & Liu, Xuan, 2009. "Spatial latent class analysis model for spatially distributed multivariate binary data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3057-3069, June.
    3. Wouterse, Bram & Huisman, Martijn & Meijboom, Bert R. & Deeg, Dorly J.H. & Polder, Johan J., 2013. "Modeling the relationship between health and health care expenditures using a latent Markov model," Journal of Health Economics, Elsevier, vol. 32(2), pages 423-439.
    4. Kari R. Hart & Teng Fei & John J. Hanfelt, 2021. "Scalable and robust latent trajectory class analysis using artificial likelihood," Biometrics, The International Biometric Society, vol. 77(3), pages 1118-1128, September.
    5. James C. Slaughter & Amy H. Herring & John M. Thorp, 2009. "A Bayesian Latent Variable Mixture Model for Longitudinal Fetal Growth," Biometrics, The International Biometric Society, vol. 65(4), pages 1233-1242, December.
    6. Beth A. Reboussin & Nicholas S. Ialongo, 2010. "Latent transition models with latent class predictors: attention deficit hyperactivity disorder subtypes and high school marijuana use," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 145-164, January.
    7. Julia Y. Lin & Thomas R. Ten Have & Michael R. Elliott, 2009. "Nested Markov Compliance Class Model in the Presence of Time-Varying Noncompliance," Biometrics, The International Biometric Society, vol. 65(2), pages 505-513, June.
    8. Diana L. Miglioretti, 2003. "Latent Transition Regression for Mixed Outcomes," Biometrics, The International Biometric Society, vol. 59(3), pages 710-720, September.
    9. Chih-chiang Yang, 2007. "Confirmatory and Structural Categorical Latent Variables Models," Quality & Quantity: International Journal of Methodology, Springer, vol. 41(6), pages 831-849, December.
    10. Labbe Aurelie & Bureau Alexandre & Merette Chantal, 2009. "Integration of Genetic Familial Dependence Structure in Latent Class Models," The International Journal of Biostatistics, De Gruyter, vol. 5(1), pages 1-30, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Doblhammer, Gabriele & van den Berg, Gerard J. & Fritze, Thomas, 2011. "Economic Conditions at the Time of Birth and Cognitive Abilities Late in Life: Evidence from Eleven European Countries," IZA Discussion Papers 5940, Institute of Labor Economics (IZA).

    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:bla:biomet:v:55:y:1999:i:3:p:839-845. See general information about how to correct material in RePEc.

    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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.