Abstract
Longitudinal trials involving surgical interventions commonly have subject-specific intervention times, due to constraints on the availability of surgeons and operating theatres. Moreover, the intervention often effects a discontinuous change in the mean response. We propose a nonparametric estimator for the mean response profile of longitudinal data with staggered intervention times and a discontinuity at the times of intervention, as an exploratory tool to assist the formulation of a suitable parametric model. We use an adaptation of the standard generalized additive model algorithm for estimation, with smoothing constants chosen by a cross-validation criterion. We illustrate the method using longitudinal data from a trial to assess the effect of lung resection surgery in the treatment of emphysema patients.
| Original language | English |
|---|---|
| Pages (from-to) | 479-485 |
| Number of pages | 7 |
| Journal | Biostatistics |
| Volume | 6 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1 Jul 2005 |
| Externally published | Yes |
Keywords
- Back-fitting algorithm
- Cross-validation
- Exploratory analysis
- Longitudinal trials
- Lung resection surgery
- Nonparametric estimator