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Activity Number: 452
Type: Contributed
Date/Time: Wednesday, August 6, 2014 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Epidemiology
Abstract #312168 View Presentation
Title: Validating Patterns for Longitudinal Trial Data
Author(s): Hua Fang*+ and Zhaoyang Zhang and Jingfang Huang and Chanpaul Wang and Honggang Wang
Companies: University of Massachusetts Medical School and University of Massachusetts Medical School/Dartmouth and University of Massachusetts Medical School/Dartmouth and University of Massachusetts Medical School and University of Massachusetts/Dartmouth
Keywords: validation ; longitudinal ; pattern ; multi-dimensional
Abstract:

Longitudinal trial data are typically correlated, multi-dimensional with missing data. Studies indicate that trajectory patterns can capture temporal variations in such data and therefore better understand the variability of patients' outcomes. However, identifying valid patterns is a critical step to ensure the validity of outcome studies. Although plenty of clustering methods are available, the validation indices and processes are insufficient to ease pattern recognition. We examined different validation indices and their respective performance in each typical clustering method. We enhanced or identified the most efficient indices for these methods using NIH-Funded datasets.


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