BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Iowa State University CALS LAS Web Team//sites.iastate.edu//EN
BEGIN:VEVENT
UID:20210617T190000-861-www.stat.iastate.edu
DTSTART:20210617T190000Z
SEQUENCE:0
TRANSP:OPAQUE
DTEND:20210617T200000Z
LOCATION:Zoom: https://iastate.zoom.us/j/93439147067?pwd=RjdPK3c2WHFaNGt3TW
 FETld6S3FZQT09
SUMMARY:Seminar: necessary and sufficient conditions for posterior propriet
 y for generalized linear mixed models
CLASS:PUBLIC
DESCRIPTION:Abstract: Generalized linear mixed models (GLMMs) are often use
 d to analyze non-Gaussian data arising from different studies. In Bayesian
  GLMMs\, the commonly used improper priors may yield undesirable improper 
 posterior distributions. Here we consider the popular improper uniform pri
 or to the regression coefficients and several proper or improper priors in
 cluding the widely used gamma and power priors on the variance components 
 of the random effects. We derive necessary and sufficient conditions for p
 osterior propriety for Bayesian binomial and Poisson GLMMs. Also\, we use 
 examples involving one-way and two-way random-effects models to demonstrat
 e the theoretical results.\n\nMore information at: https://www.stat.iastat
 e.edu/event/2021/seminar-necessary-and-sufficient-conditions-posterior-pro
 priety-generalized-linear-mixed\n\nZoom: https://iastate.zoom.us/j/9343914
 7067?pwd=RjdPK3c2WHFaNGt3TWFETld6S3FZQT09
DTSTAMP:20260411T182442Z
END:VEVENT
END:VCALENDAR