Literature DB >> 26032839

Responses to discussants of 'Joint modeling of survival and longitudinal non-survival data: current methods and issues. report of the DIA Bayesian joint modeling working group'.

A Lawrence Gould1, Mark Ernest Boye2, Michael J Crowther3, Joseph G Ibrahim4, George Quartey5, Sandrine Micallef6, Frederic Y Bois7,8.   

Abstract

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Year:  2015        PMID： 26032839      PMCID： PMC4682363          DOI： 10.1002/sim.6502

Source DB:  PubMed          Journal:  Stat Med        ISSN： 0277-6715            Impact factor:   2.373


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  1 in total

1.  Pattern mixture models and latent class models for the analysis of multivariate longitudinal data with informative dropouts.

Authors:  Etienne Dantan; Cécile Proust-Lima; Luc Letenneur; Helene Jacqmin-Gadda
Journal:  Int J Biostat       Date:  2008       Impact factor: 0.968
  1 in total
  2 in total

Review 1.  Joint models for longitudinal and time-to-event data: a review of reporting quality with a view to meta-analysis.

Authors:  Maria Sudell; Ruwanthi Kolamunnage-Dona; Catrin Tudur-Smith
Journal:  BMC Med Res Methodol       Date:  2016-12-05       Impact factor: 4.615

2.  Joint model robustness compared with the time-varying covariate Cox model to evaluate the association between a longitudinal marker and a time-to-event endpoint.

Authors:  Maeregu W Arisido; Laura Antolini; Davide P Bernasconi; Maria G Valsecchi; Paola Rebora
Journal:  BMC Med Res Methodol       Date:  2019-12-03       Impact factor: 4.615
  2 in total

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