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Activity Number: 194
Type: Contributed
Date/Time: Monday, August 5, 2013 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #310013
Title: A Novel Method for Analysis of Health Indices Data
Author(s): Huann-Sheng Chen and Shunpu Zhang*+
Companies: National Cancer Institute/NIH and University of Nebraska
Keywords: multidimensional scaling ; clustering ; age-adjusted mortality rates ; health indices
Abstract:

Health indices provide information to the general public on the health condition of the community. Currently, a common practice in comparing health indices is to report the observed health indices, as well as their associated standard errors. This approach provides useful information on the health condition of the geographical regions under study. However, it may not be able to provide enough information to distinguish geographical regions if the health index of interest is of certain rare disease or if the population under study is small. In this paper we propose a novel method to analyze the health index data. By projecting the health indices to a k-dimensional space, we can visually examine the similarities/dissimilarities of health indices on a k-dimensional space. We apply clustering methods to the locations of the health indices on the k-dimensional space to divide the health indices to clusters. The clusters can provide important information on health conditions of different geographical regions. Finally, we apply the proposed method to analyze the U.S. age-adjusted mortality rates for cancer and other diseases.


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