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SUMMARY:Block designs for non-normal data via conditional and marginal mod
 els - Woods\, D (Southampton)
DTSTART:20110809T134500Z
DTEND:20110809T143000Z
UID:TALK32286@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Many experiments in all areas of science\, technology and indu
 stry measure a response that cannot be adequately described by a linear mo
 del with normally distributed errors. In addition\, the further complicati
 on often arises of needing to arrange the experiment into blocks of homoge
 neous units. Examples include industrial manufacturing experiments with bi
 nary responses\, clinical trials where subjects receive multiple treatment
 s and crystallography experiments in early-stage drug discovery.\nThis tal
 k will present some new approaches to the design of such experiments\, ass
 uming both conditional (subject-specific) and marginal (population-average
 d) models. The different methods will be compared\, and some advantages an
 d disadvantages highlighted. Common issues\, including the impact of corre
 lations and the dependence of the design on the values of model parameters
 \, will also be discussed.\n\n
LOCATION:Seminar Room 1\, Newton Institute
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