JSM 2004 - Toronto

Abstract #301883

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Activity Number: 314
Type: Contributed
Date/Time: Wednesday, August 11, 2004 : 9:00 AM to 10:50 AM
Sponsor: Social Statistics Section
Abstract - #301883
Title: Spatial Data Analysis of Lung Cancer Mortalities in Texas
Author(s): Abhishek Lall*+ and Donald Albert and Ferry Butar Butar
Companies: Sam Houston State University and Sam Houston State University and Sam Houston State University
Address: Dept. of Mathematics and Statistics, Huntsville, TX, 77341,
Keywords: kriging ; variogram ; prediction ; anisotropy ; MSE
Abstract:

"Are neighboring measurements more likely to be similar in value than distant ones?" Crude rate estimate is usually unreliable due to general inaccuracy in number of reported cases in regions of smaller population. However, this estimate can be smoothened by considering the similar observations in the neighboring regions. We analyze mortalities caused by Lung Cancer across 254 counties in Texas during 1990-1997 and try to predict the data at certain locations. We then compare the predicted values against the actual sampled data and examine the spatial dependency of the sampled data. We use the process of kriging to accomplish the objectives. An experimental variogram is constructed, which is run through various testing steps to make it as optimal as possible. This variogram is later used to determine the optimal assigned weights. Using these weights, a minimum error variance linear estimate is constructed at a location where the true value is unknown.

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