Document Detail

Unified Computational Methods for Regression Analysis of Zero-Inflated and Bound-Inflated Data.
MedLine Citation:
PMID:  20228950     Owner:  NLM     Status:  Publisher    
Bounded data with excess observations at the boundary are common in many areas of application. Various individual cases of inflated mixture models have been studied in the literature for bound-inflated data, yet the computational methods have been developed separately for each type of model. In this article we use a common framework for computing these models, and expand the range of models for both discrete and semi-continuous data with point inflation at the lower boundary. The quasi-Newton and EM algorithms are adapted and compared for estimation of model parameters. The numerical Hessian and generalized Louis method are investigated as means for computing standard errors after optimization. Correlated data are included in this framework via generalized estimating equations. The estimation of parameters and effectiveness of standard errors are demonstrated through simulation and in the analysis of data from an ultrasound bioeffect study. The unified approach enables reliable computation for a wide class of inflated mixture models and comparison of competing models.
Yan Yang; Douglas Simpson
Publication Detail:
Journal Detail:
Title:  Computational statistics & data analysis     Volume:  54     ISSN:  0167-9473     ISO Abbreviation:  -     Publication Date:  2010 Jun 
Date Detail:
Created Date:  2010-7-13     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100960938     Medline TA:  Comput Stat Data Anal     Country:  -    
Other Details:
Languages:  ENG     Pagination:  1525-1534     Citation Subset:  -    
Department of Mathematics and Statistics, Arizona State University, Wexler Hall, Tempe, AZ 85287, USA.
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Grant Support
R01 EB002641-06//NIBIB NIH HHS

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