JSM 2003 Online Program

Abstract #300818

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Activity Number:	392
Type:	Invited
Date/Time:	Wednesday, August 6, 2003 : 2:00 PM to 3:50 PM
Sponsor:	ENAR
Abstract - #300818
Title:	Recursive Partitioning with a Multivariate Dependent
Author(s):	Douglas M. Hawkins*+
Companies:	University of Minnesota
Address:	School of Statistics, Minneapolis, MN, 55455,
Keywords:	dendrogram ; Type B ; FIRM
Abstract:	Recursive partitioning is a valuable tool for exploration of large data sets. Its ability to handle such complications as mixtures of mechanisms, nonadditivity and nonlinearity has been established in the case of a univariate dependent variable. Many important problems, however, involve multiple dependent measures. It is well known in the more traditional model settings that a multivariate analysis can yield insights that are missed by a collection of separate univariate analyses of the independent variables. This is equally true in modeling by recursive partitioning. We illustrate this with multivariate FIRM analyses of a clinical data set.

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