![](/images/graphics-bg.png)
Alternatives to Mixture Model Analysis of Correlated Binomial Data
Joint Authors
Sabo, Roy
Chaganty, N. Rao
Deng, Yihao
Source
ISRN Probability and Statistics
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-05-28
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
While univariate instances of binomial data are readily handled with generalized linear models, cases of multivariate or repeated measure binomial data are complicated by the possibility of correlated responses.
Likelihood-based estimation can be applied by using mixture distribution models, though this approach can present computational challenges.
The logistic transformation can be used to bypass these concerns and allow for alternative estimating procedures.
One popular alternative is the generalized estimating equation (GEE) method, though systematic errors can lead to infeasible correlation estimates or nonconvergence problems.
Our approach is the coupling of quasileast squares (QLSs) method with a rarely used matrix factorization, which achieves a simplified estimation platform—as compared to the mixture model approach—and does not suffer from the convergence problems in GEE method.
A noncontrived example is provided that shows the mechanical breakdown of GEE using several statistical software packages and highlights the usefulness of the QLS approach.
American Psychological Association (APA)
Chaganty, N. Rao& Sabo, Roy& Deng, Yihao. 2012. Alternatives to Mixture Model Analysis of Correlated Binomial Data. ISRN Probability and Statistics،Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-506238
Modern Language Association (MLA)
Chaganty, N. Rao…[et al.]. Alternatives to Mixture Model Analysis of Correlated Binomial Data. ISRN Probability and Statistics No. 2012 (2012), pp.1-10.
https://search.emarefa.net/detail/BIM-506238
American Medical Association (AMA)
Chaganty, N. Rao& Sabo, Roy& Deng, Yihao. Alternatives to Mixture Model Analysis of Correlated Binomial Data. ISRN Probability and Statistics. 2012. Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-506238
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-506238