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Activity Number:
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109
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #309697 |
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Title:
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Analyzing Pressure Ulcer Development of 36 Nursing Homes Using Bayesian Hierarchical Modeling
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Author(s):
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Jing Zhang*+ and Zhuoqiong (Chong) He
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Companies:
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University of Missouri-Columbia and University of Missouri-Columbia
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Address:
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510 High Street Apt 316, Columbia, MO, 65201,
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Keywords:
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Hierarchical ; logistic regression ; MCMC
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Abstract:
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Pressure ulcer development is an important measurement in judging the quality of nursing service, therefore it is an interesting research topic to find out the effect of nursing homes in the measurements of ulcer development rates. A lot of different methods have been used, including traditional logistic regression, Bayesian Hierarchical modeling and semiparametric approaches. In this report we use Bayesian Hierarchical Models and apply MCMC algorithm to predict the performance of 36 nursing homes in term of pressure ulcer development of the residents in these institutes. Bayesian approach provides posterior distributions besides estimates and predictions, therefore we could develop different criteria for detecting the nursing homes that are providing problematic nursing services. We also performed cross validation to evaluate the predictive ability of the Bayesian Hierarchic model.
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