Profile clustering in clinical trials with longitudinal and functional data methods. Issue 3 (4th May 2019)

• Record Type: Journal Article
• Authors: Gong, Hangjun; Xun, Xiaolei; Zhou, Yingchun
• Is Part Of: Journal of biopharmaceutical statistics. Volume 29:Issue 3(2019)
• Page Start: 541
• Page End: 557
• Publication Date: 2019-05-04
• Subjects: Clustering analysis -- functional data -- longitudinal data -- nonparametric -- profile data; Pharmacy -- Statistical methods -- Periodicals; Drugs -- Testing -- Statistical methods -- Periodicals; Biometry -- Periodicals; Biopharmaceutics -- Periodicals; Pharmacokinetics -- Periodicals; 615.19
• DOI: 10.1080/10543406.2019.1572614
• Languages: English
• ISSNs: 1054-3406

Abstract

ABSTRACT: Repeated measurements are widely encountered in medical or pharmaceutical studies, which can be analyzed by both longitudinal data and functional data analysis methods, particularly when the underlying process is continuous and the number of measurement points is not too small. Motivated by real problems of clustering patient profiles in clinical trials, this paper gives an overview of the clustering methods for repeated measurement data and compares three longitudinal data methods and two functional data methods with extensive simulation studies. Methods with appropriate properties are applied to the real data to produce interpretable results.