Spatial Poisson regression : Bayesian approach correcting for measurement error with applications.

Under and over reporting is a common problem in social science research, adverse events associated with drug use, and many other areas of research. Furthermore, overdispersion is another common problem that plagues count data. McBride (2006) proposed a Bayesian Poisson regression model which accounts for overdispersion in count data. We extend this model by adding parameters to accommodate the problems associated with under and over reporting in the count data. We then study the model's coverage, power, accuracy of point estimates, and credible set widths through simulation using a spatial lattice grid. We find that our proposed model produces reliable point estimates and reasonable credible set widths, coverage, and power. We also provide two examples of the models use: disease mapping of habitat burglary from the city of Waco Texas and an analysis of sports data similar to that of Albert's (1992) analysis of homerun data. Research questions of interest are answered using the subset selection procedure proposed by Bratcher and Bhalla (1974), used by Hamilton, Bratcher, and Stamey (2008) and Stamey, Bratcher, and Young (2007), to demonstrate the ease of use for combining the our model developed here and the subset selection procedure itself, as was also done in McBride (2006).

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Doctoral

Grantor

Baylor University.

Year dc:date.issued

2010

Author dc:creator

• Atkinson, William H., 1980-

Advisor dc:contributor.advisor

• Bratcher, Thomas L.

• Statistics.
• Statistical modeling.
• Bayesian methods.

Statement dc:rights

• Baylor University works are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. Contact libraryquestions@baylor.edu for inquiries about permission.

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/2104/8019

OAI identifier oai:identifier

oai:baylor-ir.tdl.org:2104/8019