File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Bayesian goodness-of-fit test for censored data

TitleBayesian goodness-of-fit test for censored data
Authors
KeywordsBayesian inference
Failure time data
Hypothesis testing
Model diagnostic
Pearson statistic
Posterior sample
Issue Date2009
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jspi
Citation
Journal Of Statistical Planning And Inference, 2009, v. 139 n. 4, p. 1474-1483 How to Cite?
AbstractWe propose a Bayesian computation and inference method for the Pearson-type chi-squared goodness-of-fit test with right-censored survival data. Our test statistic is derived from the classical Pearson chi-squared test using the differences between the observed and expected counts in the partitioned bins. In the Bayesian paradigm, we generate posterior samples of the model parameter using the Markov chain Monte Carlo procedure. By replacing the maximum likelihood estimator in the quadratic form with a random observation from the posterior distribution of the model parameter, we can easily construct a chi-squared test statistic. The degrees of freedom of the test equal the number of bins and thus is independent of the dimensionality of the underlying parameter vector. The test statistic recovers the conventional Pearson-type chi-squared structure. Moreover, the proposed algorithm circumvents the burden of evaluating the Fisher information matrix, its inverse and the rank of the variance-covariance matrix. We examine the proposed model diagnostic method using simulation studies and illustrate it with a real data set from a prostate cancer study. © 2008 Elsevier B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/139726
ISSN
2015 Impact Factor: 0.727
2015 SCImago Journal Rankings: 1.090
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYin, Gen_HK
dc.date.accessioned2011-09-23T05:54:48Z-
dc.date.available2011-09-23T05:54:48Z-
dc.date.issued2009en_HK
dc.identifier.citationJournal Of Statistical Planning And Inference, 2009, v. 139 n. 4, p. 1474-1483en_HK
dc.identifier.issn0378-3758en_HK
dc.identifier.urihttp://hdl.handle.net/10722/139726-
dc.description.abstractWe propose a Bayesian computation and inference method for the Pearson-type chi-squared goodness-of-fit test with right-censored survival data. Our test statistic is derived from the classical Pearson chi-squared test using the differences between the observed and expected counts in the partitioned bins. In the Bayesian paradigm, we generate posterior samples of the model parameter using the Markov chain Monte Carlo procedure. By replacing the maximum likelihood estimator in the quadratic form with a random observation from the posterior distribution of the model parameter, we can easily construct a chi-squared test statistic. The degrees of freedom of the test equal the number of bins and thus is independent of the dimensionality of the underlying parameter vector. The test statistic recovers the conventional Pearson-type chi-squared structure. Moreover, the proposed algorithm circumvents the burden of evaluating the Fisher information matrix, its inverse and the rank of the variance-covariance matrix. We examine the proposed model diagnostic method using simulation studies and illustrate it with a real data set from a prostate cancer study. © 2008 Elsevier B.V. All rights reserved.en_HK
dc.languageengen_US
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jspien_HK
dc.relation.ispartofJournal of Statistical Planning and Inferenceen_HK
dc.subjectBayesian inferenceen_HK
dc.subjectFailure time dataen_HK
dc.subjectHypothesis testingen_HK
dc.subjectModel diagnosticen_HK
dc.subjectPearson statisticen_HK
dc.subjectPosterior sampleen_HK
dc.titleBayesian goodness-of-fit test for censored dataen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0378-3758&volume=139&issue=4&spage=1474&epage=1483&date=2009&atitle=Bayesian+goodness-of-fit+test+for+censored+data-
dc.identifier.emailYin, G: gyin@hku.hken_HK
dc.identifier.authorityYin, G=rp00831en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jspi.2008.07.020en_HK
dc.identifier.scopuseid_2-s2.0-57749210215en_HK
dc.identifier.hkuros195660en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-57749210215&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume139en_HK
dc.identifier.issue4en_HK
dc.identifier.spage1474en_HK
dc.identifier.epage1483en_HK
dc.identifier.isiWOS:000262760800017-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridYin, G=8725807500en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats