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                                   REMINDER

             CENTRE FOR MEDICAL STATISTICS

       SEMINAR SERIES on BIOSTATISTICS 2000/2001

    NO 2: Wednesday, December 13th, 2000, at 2:30 pm

   Multilevel Modelling of Nominal Data and Rankings

                                   by

               Dr Sophia Rabe-Hesketh

          (Institute of Psychiatry, London)

Unordered categorical responses are of interest in many
disciplines, examples including party voted for in an election
or treatment selected for a patient. Here the response is the
category 'selected' by an individual. Rankings arise when the
individual does not just select one category, but orders the
categories according to some criterion. Such data can be
modelled by assuming that each individual assigns 'utilities'
to the categories and 'selects' the category with the greatest
utility (nominal data) or ranks the categories according to the
utilities (rankings). For nominal data and independent utilities,
certain distributional assumptions for the utilities lead to the
well-known multinominal logit or polychotomous logistic
regression model. I will discuss extensions to this model for
rankings and for correlated utilities. If the data are multilevel,
the utilities are not just correlated within individuals but also
between the individuals in the same higher level unit or cluster.
The models represent generalisations of generalised linear
mixed models and can be estimated by maximising the marginal
likelihood using numerical integration. The method is implemented
in a Stata program called gllamm6. This work was done jointly
with Anders Skrondal.

All welcome!!

Venue:
Room 2.22, Third Floor
The MacKay Building
Keele University

http://www.keele.ac.uk
http://www.keele.ac.uk/depts/ma/seminars/medstats.html
http://www.keele.ac.uk/university/campus/maps/

____________________________

Janet Drewery
Secretary
Centre for Medical Statistics
Keele University
Staffordshire ST5 5BG
England

Email: [log in to unmask]

Tel: (01782) 583269
Fax: (01782) 583269/584268
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