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SUMMARY:Optimal design for the estimation of population location parameter
 s in nonlinear mixed effects models - Mielke\, T (Otto-von-Guericke-Univer
 sitt Magdeburg)
DTSTART:20110718T153000Z
DTEND:20110718T160000Z
UID:TALK32073@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Nonlinear mixed effects models are frequently used in the anal
 ysis of grouped data. Specially in pharmacological studies the observed in
 dividuals usually share a common response structure\, such that informatio
 n from individual responses might be merged to obtain efficient estimates.
  The mixed effects Models can be used to model population studies by assum
 ing the individual parameter vectors to be realizations of independently d
 istributed random variables\, what yields for nonlinear response functions
  of the individual parameters nontrivial models. Unfortunately\, in nonlin
 ear mixed effects models problems occur\, as there exists no closed form r
 epresentation of the likelihood-function of the observations and hence no 
 closed form of the Fisher Information. Optimal designs in nonlinear mixed 
 effects models are usually based on approximations of the Fisher Informati
 on\, such that bad approximations might lead to bad experimental designs. 
 In this talk we discuss different approaches for approximating the informa
 tion matrix and the influence of the approximations on the implied designs
  in pharmacokinetic studies. \n
LOCATION:Seminar Room 1\, Newton Institute
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