Seminario

["Carlo N. Lauro" <carlo.lauro@unina.it>]

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Dipartimento di Matematica e Statistica Università Federico II - Napoli
                      
                       Avviso di Seminario

VENERDI 29 settembre ore 10

Some new approaches in multivariate categorical data analysis


Jacqueline J. Meulman
Data Theory Group
Faculty of Social and Behavioral Science
Leiden University
The Netherlands

In this seminar we will discuss various approaches to the analysis of
multivariate categorical data. The first is a form of principal components
analysis combined with multiple correspondence analysis: in addition to the
fitting of points for individual subjects, additional points may be fitted
for groups among the subjects. There is a large emphasis on graphical
display of the results in biplots (with variables and subjects) and
triplots (with variables, subjects, and groups). The information contained
in the biplots and triplots is used to draw special graphs that identify
particular groups in the data that standout on selected variables. The
approach can also be used for data mining, and will be applied to a data
set for a large number of European countries with respect to a variety of
nonmetric variables.
The second is an extension of correspondence analysis to include the
representation of three-way data through an individual differences model,
adapted from multidimensional scaling. A particular application will be the
analysis of a longitudinal series of contingency matrices pertaining to
various infections occurring during different seasons, with infection rates
measured over a nine-year period. 
Finally, we will discuss a new approach to unidimensional scaling in
multivariate data. Here we have to deal with a combinatorial optimization
problem. The result is an optimal ordering of objects while the original
data have been transformed by monotonic spline functions. A real life data
example will demonstrate the technique to a consensus ordering of birth
control methods according to four different groups of reviewers scoring the
methods on four different criteria.

Keywords: Optimal Scaling, Correspondence Analysis, Principal Components,
Biplot, Triplot, Categorical Data, Ordinal Data, Longitudinal Data,
Multidimensional Scaling, Three-way Models, Unidimensional Scaling.

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Prof. Carlo Lauro
Dipartimento di Matematica e Statistica
Universita' degli Studi di Napoli "Federico II"
Via Cintia - Complesso Monte Sant'Angelo
I-80126 Napoli

tel.: +39 081 675189    fax: +39 081 675113
e-mail: carlo.lauro@unina.it
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