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Title: Classified functional mixed effects model prediction
In nowadays biomedical research, there has been a growing demand for making accurate prediction at subject levels. In many of these situations, data are collected as longitudinal curves and display distinct individual characteristics. Thus, prediction mechanisms accommodated with functional mixed effects models (FMEM) are useful. In this paper, we developed a classified functional mixed model prediction (CFMMP) method, which adapts classified mixed model prediction (CMMP) to the framework of FMEM. Performance of CFMMP against functional regression prediction based on simulation studies and the consistency property of CFMMP estimators are explored. Real‐world applications of CFMMP are illustrated using real world examples including data from the hormone research menstrual cycles and the diffusion tensor imaging.  more » « less
Award ID(s):
2210569
PAR ID:
10629252
Author(s) / Creator(s):
;
Publisher / Repository:
Wiley
Date Published:
Journal Name:
Statistics in Medicine
Volume:
43
Issue:
7
ISSN:
0277-6715
Page Range / eLocation ID:
1329 to 1340
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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