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Activity Number:
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331
- ASA Biopharmaceutical Section Student Paper Award Competition
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Type:
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Contributed
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Date/Time:
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Tuesday, August 9, 2022 : 2:00 PM to 3:50 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #322682
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Title:
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A New Clustering Method for Longitudinal Data
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Author(s):
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Junyi Zhou* and Ying Zhang and Wanzhu Tu
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Companies:
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Amgen and University of Nebraska Medical Center and INDIANA UNIVERSITY
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Keywords:
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B-splines;
Clustering;
Dissimilarity metric;
Longitudinal data;
Multiple-outcomes
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Abstract:
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Longitudinal data clustering is challenging because the grouping has to account for the similarity of individual trajectories instead of the localized closeness at given time points. This paper puts forward a hierarchical agglomerative clustering method based on B-spline curve-fitting of repeatedly measured outcomes and a dissimilarity metric that quantifies the cost of merging two distinct groups of curves. Extensive simulations showed that the proposed method had superior clustering performance in terms of accuracy and efficiency. Importantly, the method is extendable to situations of multiple outcome clustering without much increased computational burden. To illustrate the use of the proposed clustering method, we analyzed data from two clinical studies.
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Authors who are presenting talks have a * after their name.
