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Article: Applications of additive semivarying coefficient models: Monthly suicide data from Hong Kong

TitleApplications of additive semivarying coefficient models: Monthly suicide data from Hong Kong
Authors
KeywordsLocal polynomial model
Longitudinal data
Semivarying coefficients
Suicide
Issue Date2007
PublisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/BIOM
Citation
Biometrics, 2007, v. 63 n. 3, p. 708-713 How to Cite?
AbstractA semivarying coefficient model for the monthly numbers of suicides in Hong Kong is developed and a new estimation procedure for estimating the parametric component is proposed. The estimators are examined in a small simulation study and fitted to monthly suicide data to estimate a nonparametric long-term trend and parametric seasonal and socioeconomic effects. Fitting the model detected interpretable structure in the data that is consistent with that driving public health policy. While exploratory, the analysis motivates the collection of more detailed data and the development of more sophisticated models to help determine target groups and strategies to reduce the suicide rate in Hong Kong. © 2006, The International Biometric Society.
Persistent Identifierhttp://hdl.handle.net/10722/87785
ISSN
2014 Impact Factor: 1.568
2014 SCImago Journal Rankings: 2.046
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorHuggins, RMen_HK
dc.contributor.authorHall, Pen_HK
dc.contributor.authorYip, PSFen_HK
dc.contributor.authorBui, QMen_HK
dc.date.accessioned2010-09-06T09:34:24Z-
dc.date.available2010-09-06T09:34:24Z-
dc.date.issued2007en_HK
dc.identifier.citationBiometrics, 2007, v. 63 n. 3, p. 708-713en_HK
dc.identifier.issn0006-341Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/87785-
dc.description.abstractA semivarying coefficient model for the monthly numbers of suicides in Hong Kong is developed and a new estimation procedure for estimating the parametric component is proposed. The estimators are examined in a small simulation study and fitted to monthly suicide data to estimate a nonparametric long-term trend and parametric seasonal and socioeconomic effects. Fitting the model detected interpretable structure in the data that is consistent with that driving public health policy. While exploratory, the analysis motivates the collection of more detailed data and the development of more sophisticated models to help determine target groups and strategies to reduce the suicide rate in Hong Kong. © 2006, The International Biometric Society.en_HK
dc.languageengen_HK
dc.publisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/BIOMen_HK
dc.relation.ispartofBiometricsen_HK
dc.rightsBiometrics. Copyright © Blackwell Publishing Ltd.en_HK
dc.subjectLocal polynomial modelen_HK
dc.subjectLongitudinal dataen_HK
dc.subjectSemivarying coefficientsen_HK
dc.subjectSuicideen_HK
dc.titleApplications of additive semivarying coefficient models: Monthly suicide data from Hong Kongen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0006-341X&volume=63 &issue=3&spage=708&epage=13&date=2007&atitle=Applications+Of+Additive+Semivarying+Coefficient+Models:+Monthly+Suicide+Data+From+Hong+Kong.+en_HK
dc.identifier.emailYip, PSF: sfpyip@hku.hken_HK
dc.identifier.authorityYip, PSF=rp00596en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/j.1541-0420.2006.00727.xen_HK
dc.identifier.pmid17825004-
dc.identifier.scopuseid_2-s2.0-34548401261en_HK
dc.identifier.hkuros152811en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34548401261&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume63en_HK
dc.identifier.issue3en_HK
dc.identifier.spage708en_HK
dc.identifier.epage713en_HK
dc.identifier.isiWOS:000248947200011-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridHuggins, RM=7102879186en_HK
dc.identifier.scopusauthoridHall, P=7403695286en_HK
dc.identifier.scopusauthoridYip, PSF=7102503720en_HK
dc.identifier.scopusauthoridBui, QM=7003959081en_HK
dc.identifier.citeulike1618439-

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