Bayesian ridge estimation of age-period-cohort models

dc.contributor.advisorPowers, Daniel A.
dc.creatorXu, Minleen
dc.date.accessioned2014-10-02T21:25:22Zen
dc.date.accessioned2018-01-22T22:26:40Z
dc.date.available2018-01-22T22:26:40Z
dc.date.issued2014-08en
dc.date.submittedAugust 2014en
dc.date.updated2014-10-02T21:25:22Zen
dc.descriptiontexten
dc.description.abstractAge-Period-Cohort models offer a useful framework to study trends of time-specific phenomena in various areas. Yet the perfect linear relationship among age, period, and cohort induces a singular design matrix and brings about the identification issue of age, period, and cohort model due to the identity Cohort = Period -- Age. Over the last few decades, multiple methods have been proposed to cope with the identification issue, e.g., the intrinsic estimator (IE), which may be viewed as a limiting form of ridge regression. This study views the ridge estimator from a Bayesian perspective by introducing a prior distribution(s) for the ridge parameter(s). Data used in this study describe the incidence rate of cervical cancer among Ontario women from 1960 to 1994. Results indicate that a Bayesian ridge model with a common prior for the ridge parameter yields estimates of age, period, and cohort effects similar to those based on the intrinsic estimator and to those based on a ridge estimator. The performance of Bayesian models with distinctive priors for the ridge parameters of age, period, and cohort effects is affected more by the choice of prior distributions. In sum, a Bayesian ridge model is an alternative way to deal with the identification problem of age, period, and cohort model. Future studies should further investigate the influences of different prior choices on Bayesian ridge models.en
dc.description.departmentStatisticsen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/2152/26250en
dc.language.isoenen
dc.subjectBayesian estimationen
dc.subjectRidge estimatoren
dc.subjectAge-period-cohort modelsen
dc.titleBayesian ridge estimation of age-period-cohort modelsen
dc.typeThesisen

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