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 language | English |
|---|---|
| Pages (from-to) | 176-184 |
| Number of pages | 9 |
| Journal | Statistics in Biopharmaceutical Research |
| Volume | 10 |
| Issue number | 3 |
| DOIs | |
| State | Published - 3 Jul 2018 |
Keywords
- Clinical trials
- Functional data
- Functional mixed effects model
- Penalized spline
- Repeated measurements