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SUMMARY:Latent Mixture Quantile Regression for Longitudinal Data - Dr. Bo 
 Fu\, School of Community-Based Medicine\, University of Manchester
DTSTART:20120214T143000Z
DTEND:20120214T153000Z
UID:TALK35107@talks.cam.ac.uk
CONTACT:Li Su
DESCRIPTION:\n\nThis paper proposes mixture median and quantile models for
  describing latent\ngrowth curves of longitudinal outcomes. The models exh
 ibit the different latent\nclasses of evolution of the underlying outcome 
 process. The mixture median model\ncan be used as a robust alternative to 
 the Gaussian likelihood based latent class\nmodel for skewed data\, and th
 e quantile models provide a complete regression\npicture for investigating
  the latent class structure at different quantiles. The\nwithin-subject co
 rrelation is incorporated by a marginal approach based on the\nidea of wei
 ghting. The weighted estimating equations for the model parameters\nare gi
 ven\, and a penalized weighted loss function is defined to select the opti
 mal\nnumber of latent classes. 
LOCATION:Large  Seminar Room\, 1st Floor\, Institute of Public Health\, Un
 iversity Forvie Site\, Robinson Way\, Cambridge
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