Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/10506
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMwambi, H.-
dc.contributor.authorRamroop, S.-
dc.contributor.authorWhite, L.J.-
dc.contributor.authorOkiro, E.A.-
dc.contributor.authorNokes, D.J.-
dc.contributor.authorSHKEDY, Ziv-
dc.contributor.authorMOLENBERGHS, Geert-
dc.date.accessioned2010-02-19T08:49:12Z-
dc.date.available2010-02-19T08:49:12Z-
dc.date.issued2011-
dc.identifier.citationSTATISTICAL METHODS IN MEDICAL RESEARCH, 20(5), p. 551-570-
dc.identifier.issn0962-2802-
dc.identifier.urihttp://hdl.handle.net/1942/10506-
dc.description.abstractThis paper aims to develop a probability-based model involving the use of direct likelihood formulation and generalised linear modelling in order to estimate important disease parameters from real data. The force of infection and the recovery rate or per capita loss of infection are the parameters of interest. The problem of dealing with time-varying disease parameters is also addressed in the paper by fitting piecewise constant parameters over time. The findings of the current paper are comparable and similar to estimates from an independent approach suggested by White et al.21 that employed Bayesian MCMC modelling via WinBUGS.-
dc.description.sponsorshipThe authors gratefully acknowledge the financial support from The Wellcome Trust (Grant No. 061584), and the IUAP research network Nr. P5/24 of the Belgian Government (Belgian Science Policy). Shaun Ramroop would like to thank the NRF of South Africa for funding his PhD work (THUTHUKA-Researchers in training Ref. No: TTK2005081700004). Mahidol-Oxford Tropical Medicine Research Unit is funded by the Wellcome Trust of Great Britain. This article is published with the permission of the Director of KEMRI.-
dc.language.isoen-
dc.publisherSAGE PUBLICATIONS LTD-
dc.rights© The Author(s), 2011. Reprints and permissions-
dc.titleA frequentist approach to estimating the force of infection and the recovery rate for a respiratory disease among infants in coastal Kenya-
dc.typeJournal Contribution-
dc.identifier.epage570-
dc.identifier.issue5-
dc.identifier.spage551-
dc.identifier.volume20-
local.bibliographicCitation.jcatA1-
dc.description.notesH. Mwambi1, S. Ramroop: University of KwaZulu-Natal, P/Bag X01 Scottsville, PMB, SouthAfrica - Ziv Shkedy, and Geert Molenberghs: Hasselt University, Agoralaan 1, B-3590, Diepenbeek,Belgium-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.bibliographicCitation.oldjcatA1-
dc.identifier.doi10.1177/0962280208098666-
item.fulltextWith Fulltext-
item.accessRightsOpen Access-
item.contributorMwambi, H.-
item.contributorRamroop, S.-
item.contributorWhite, L.J.-
item.contributorOkiro, E.A.-
item.contributorNokes, D.J.-
item.contributorSHKEDY, Ziv-
item.contributorMOLENBERGHS, Geert-
item.fullcitationMwambi, H.; Ramroop, S.; White, L.J.; Okiro, E.A.; Nokes, D.J.; SHKEDY, Ziv & MOLENBERGHS, Geert (2011) A frequentist approach to estimating the force of infection and the recovery rate for a respiratory disease among infants in coastal Kenya. In: STATISTICAL METHODS IN MEDICAL RESEARCH, 20(5), p. 551-570.-
crisitem.journal.issn0962-2802-
crisitem.journal.eissn1477-0334-
Appears in Collections:Research publications
Files in This Item:
File Description SizeFormat 
SMMR9thRev[1].pdfPeer-reviewed author version193.44 kBAdobe PDFView/Open
10.1177_0962280210385749.pdf
  Restricted Access		Published version176.27 kBAdobe PDFView/Open    Request a copy
Show simple item record

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.