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SUMMARY:Generalized estimating equations for censored data - Daniel Farewe
 ll\, Cardiff University
DTSTART:20091110T143000Z
DTEND:20091110T153000Z
UID:TALK19054@talks.cam.ac.uk
CONTACT:Michael Sweeting
DESCRIPTION:Models for longitudinal measurements truncated by possibly inf
 ormative dropout tend to be mathematically complex or computationally dema
 nding. Diggle et al. (2007\, JRSSC)\n recently proposed an alternative usi
 ng simple ideas from event-history analysis (where censoring is commonplac
 e) to yield moment-based estimators for balanced\, continuous longitudinal
  data. Here we show that their estimate may be derived as a limit of gener
 alized estimating equations. We use this fact to extend their ideas to mor
 e general longitudinal contexts (unbalanced\, categorical data\, for examp
 le) while maintaining simplicity of understanding and implementation.
LOCATION:Large Seminar Room\, 1st Floor\, Institute of Public Health\, Uni
 versity Forvie Site\, Robinson Way\, Cambridge
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