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Model-based cluster analysis for structured data

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If you have a question about this talk, please contact Michael Sweeting.

Cluster analysis is concerned with allocating subjects to unknown groups or subpopulations. Often the data that are subject to clustering are structured in that they consist of multiple measures taken on the scale and referenced by time (longitudinal data), condition (repeated measures data) or underlying concept (factor models). In this talk I will introduce model-based clustering approaches suitable for such structured data. In particular I will introduce a mixture of factor analyzers model and growth mixture modelling and demonstrate these approaches by some literature examples.

This talk is part of the MRC Biostatistics Unit Seminars series.

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