Change point models for cognitive tests using semi-parametric maximum likelihood
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Bauwens, Luc & Rombouts, Jeroen V.K., 2012.
"On marginal likelihood computation in change-point models,"
Computational Statistics & Data Analysis,
Elsevier, vol. 56(11), pages 3415-3429.
- BAUWENS, Luc & ROMBOUTS, Jeroen, 2009. "On marginal likelihood computation in change-point models," CORE Discussion Papers 2009061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & ROMBOUTS, Jeroen VK, 2012. "On marginal likelihood computation in change-point models," CORE Discussion Papers RP 2403, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & Jeroen V.K. Rombouts, 2009. "On Marginal Likelihood Computation in Change-point Models," Cahiers de recherche 0942, CIRPEE.
- Daniel Rudoy & Shelten G. Yuen & Robert D. Howe & Patrick J. Wolfe, 2010. "Bayesian change-point analysis for atomic force microscopy and soft material indentation," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(4), pages 573-593.
- Sonja Greven & Thomas Kneib, 2010. "On the behaviour of marginal and conditional AIC in linear mixed models," Biometrika, Biometrika Trust, vol. 97(4), pages 773-789.
- Chiu, Grace & Lockhart, Richard & Routledge, Richard, 2006. "Bent-Cable Regression Theory and Applications," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 542-553, June.
- G. Muniz Terrera & A. van den Hout & F. E. Matthews, 2011. "Random change point models: investigating cognitive decline in the presence of missing data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(4), pages 705-716, November.
- Stasinopoulos, D. M. & Rigby, R. A., 1992. "Detecting break points in generalised linear models," Computational Statistics & Data Analysis, Elsevier, vol. 13(4), pages 461-471, May.
- Hall, Charles B. & Ying, Jun & Kuo, Lynn & Lipton, Richard B., 2003. "Bayesian and profile likelihood change point methods for modeling cognitive function over time," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 91-109, February.
More about this item
KeywordsBeta-binomial distribution; Latent class model; Mini-mental state examination; Random-effects model;
StatisticsAccess and download statistics
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:eee:csdana:v:57:y:2013:i:1:p:684-698. 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: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/csda .
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 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.