Bayesian blockwise inference for joint models of longitudinal and multistate data with application to longitudinal multimorbidity analysis.

Saved in:
Bibliographic Details
Title: Bayesian blockwise inference for joint models of longitudinal and multistate data with application to longitudinal multimorbidity analysis.
Authors: Chen S; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK., Alvares D; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK., Jackson C; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK., Marshall T; Institute of Applied Health Research, University of Birmingham, Birmingham, UK., Nirantharakumar K; Institute of Applied Health Research, University of Birmingham, Birmingham, UK., Richardson S; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK., Saunders CL; Department of Public Health and Primary Care, University of Cambridge, Cambridge, Cambridgeshire, UK., Barrett JK; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Source: Statistical methods in medical research [Stat Methods Med Res] 2024 Nov; Vol. 33 (11-12), pp. 2027-2042. Date of Electronic Publication: 2024 Oct 21.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: SAGE Publications Country of Publication: England NLM ID: 9212457 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1477-0334 (Electronic) Linking ISSN: 09622802 NLM ISO Abbreviation: Stat Methods Med Res Subsets: MEDLINE
Database: MEDLINE Ultimate
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 39428891
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Bayesian blockwise inference for joint models of longitudinal and multistate data with application to longitudinal multimorbidity analysis.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Chen+S%22">Chen S</searchLink>; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.<br /><searchLink fieldCode="AU" term="%22Alvares+D%22">Alvares D</searchLink>; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.<br /><searchLink fieldCode="AU" term="%22Jackson+C%22">Jackson C</searchLink>; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.<br /><searchLink fieldCode="AU" term="%22Marshall+T%22">Marshall T</searchLink>; Institute of Applied Health Research, University of Birmingham, Birmingham, UK.<br /><searchLink fieldCode="AU" term="%22Nirantharakumar+K%22">Nirantharakumar K</searchLink>; Institute of Applied Health Research, University of Birmingham, Birmingham, UK.<br /><searchLink fieldCode="AU" term="%22Richardson+S%22">Richardson S</searchLink>; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.<br /><searchLink fieldCode="AU" term="%22Saunders+CL%22">Saunders CL</searchLink>; Department of Public Health and Primary Care, University of Cambridge, Cambridge, Cambridgeshire, UK.<br /><searchLink fieldCode="AU" term="%22Barrett+JK%22">Barrett JK</searchLink>; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%229212457%22">Statistical methods in medical research</searchLink> [Stat Methods Med Res] 2024 Nov; Vol. 33 (11-12), pp. 2027-2042. <i>Date of Electronic Publication: </i>2024 Oct 21.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article; Research Support, Non-U.S. Gov't
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22SAGE+Publications%22">SAGE Publications </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>9212457 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1477-0334 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2209622802%22">09622802 </searchLink><i>NLM ISO Abbreviation: </i>Stat Methods Med Res <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=39428891
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1177/09622802241281959
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 2027
    Titles:
      – TitleFull: Bayesian blockwise inference for joint models of longitudinal and multistate data with application to longitudinal multimorbidity analysis.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Chen S
      – PersonEntity:
          Name:
            NameFull: Alvares D
      – PersonEntity:
          Name:
            NameFull: Jackson C
      – PersonEntity:
          Name:
            NameFull: Marshall T
      – PersonEntity:
          Name:
            NameFull: Nirantharakumar K
      – PersonEntity:
          Name:
            NameFull: Richardson S
      – PersonEntity:
          Name:
            NameFull: Saunders CL
      – PersonEntity:
          Name:
            NameFull: Barrett JK
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 11
              Text: 2024 Nov
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-electronic
              Value: 1477-0334
          Numbering:
            – Type: volume
              Value: 33
            – Type: issue
              Value: 11-12
          Titles:
            – TitleFull: Statistical methods in medical research
              Type: main
ResultId 1