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Activity Number:
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202
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Type:
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Contributed
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Date/Time:
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Monday, August 7, 2006 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #306972 |
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Title:
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Repeated Measures Mixture Modeling with Applications to Postmortem Tissue Studies in Schizophrenia
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Author(s):
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Zhuoxin Sun*+ and Ori Rosen and Allan R. Sampson
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Companies:
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Dana-Farber Cancer Institute and The University of Texas at El Paso and University of Pittsburgh
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Address:
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44 Binney Street, Boston, MA, 02115,
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Keywords:
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MCMC ; mixture models ; repeated measures ; schizophrenia
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Abstract:
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In some neurological postmortem brain tissue studies, repeated measures are observed. These observations are taken on the same subject and are correlated within the subject. Furthermore, each observation can be viewed as coming from one of a pre-specified number of populations where each population corresponds to a possible type of neuron. A mixture model to model such repeated data will be presented. In this model, the mixture components are linear regressions, and the component-indicator variables are logits with random effects. The within-subject observations are taken to be correlated through the component indicator random variables. Inference is facilitated by sampling from the posterior distribution of the parameters via MCMC methods. The model is applied to a postmortem brain tissue study to examine the differences in neuron volumes between schizophrenic and control subjects.
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