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dc.contributor.advisorStamey, James D.
dc.contributor.authorPowers, Stephanie L.
dc.contributor.otherBaylor University. Dept. of Statistical Sciences.en
dc.date.accessioned2009-07-01T17:02:34Z
dc.date.available2009-07-01T17:02:34Z
dc.date.copyright2009-05
dc.date.issued2009-07-01T17:02:34Z
dc.identifier.urihttp://hdl.handle.net/2104/5355
dc.descriptionIncludes bibliographical references (p. 175-178).en
dc.description.abstractResponse partial missingness is a problem in studies conducted in a variety of disciplines. We investigate the impact ignoring response partial missingness has on determining a subset of significant covariates in non-linear regression. In particular, we consider non-differential misclassification in logistic regression and non-differential under-reporting in Poisson regression. Differential misclassification and differential under-reporting are also addressed but in less detail. We then develop a Bayesian approach to select significant covariates while accounting for the partial missingness. Examples of response partial missingness in which the variable selection method is applied include determining the factors that contribute to whether or not an individual will stop smoking and how many days an individual is absent from work.en
dc.description.statementofresponsibilityby Stephanie Powers.en
dc.format.extentxv, 178 p. : ill.en
dc.format.extent43516031 bytes
dc.format.extent158501 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen
dc.rightsBaylor University theses 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 librarywebmaster@baylor.edu for inquiries about permission.en
dc.subjectBayesian statistical decision theory.en
dc.subjectRegression analysis.en
dc.subjectMissing observations (Statistics).en
dc.subjectError analysis (Mathematics).en
dc.subjectPoisson distribution.en
dc.titleBayesian approach to inference and variable selection for misclassified and under-reported response models.en
dc.typeThesisen
dc.description.degreePh.D.en
dc.rights.accessrightsBaylor University access onlyen
dc.contributor.departmentStatistical Sciences.en


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