Functional Mixed Effects Model for the Analysis of Dose-Titration Studies

Ji Chen, David Ohlssen, Yingchun Zhou

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Functional data analysis, which analyzes data that can be represented by curves or images, has many potential applications in clinical trials. Motivated by a real example, this study constructs a functional mixed effects model for analyzing a clinical outcome that is observed continuously over a long period of time. A penalized spline (P-spline)-based method is applied to obtain the estimators of the mean function and the time-varying coefficients. Simulation studies are conducted to investigate the consistency, efficiency, and robustness of the method. To illustrate the use of the method, a real data analysis is performed and produces interpretable results.

Original languageEnglish
Pages (from-to)176-184
Number of pages9
JournalStatistics in Biopharmaceutical Research
Volume10
Issue number3
DOIs
StatePublished - 3 Jul 2018

Keywords

  • Clinical trials
  • Functional data
  • Functional mixed effects model
  • Penalized spline
  • Repeated measurements

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