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 (US) |
|---|---|
| Pages (from-to) | 479-485 |
| Number of pages | 7 |
| Journal | Biostatistics |
| Volume | 6 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jul 2005 |
| Externally published | Yes |
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Keywords
- Back-fitting algorithm
- Cross-validation
- Exploratory analysis
- Longitudinal trials
- Lung resection surgery
- Nonparametric estimator
ASJC Scopus subject areas
- Medicine(all)
- Statistics and Probability
- Statistics, Probability and Uncertainty
Cite this
Exploratory analysis of longitudinal trials with staggered intervention times. / Sousa, Inês; Chetwynd, Amanda G.; Diggle, Peter J.
In: Biostatistics, Vol. 6, No. 3, 07.2005, p. 479-485.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Exploratory analysis of longitudinal trials with staggered intervention times
AU - Sousa, Inês
AU - Chetwynd, Amanda G.
AU - Diggle, Peter J.
PY - 2005/7
Y1 - 2005/7
N2 - 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.
AB - 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.
KW - Back-fitting algorithm
KW - Cross-validation
KW - Exploratory analysis
KW - Longitudinal trials
KW - Lung resection surgery
KW - Nonparametric estimator
UR - http://www.scopus.com/inward/record.url?scp=26644454398&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=26644454398&partnerID=8YFLogxK
U2 - 10.1093/biostatistics/kxi023
DO - 10.1093/biostatistics/kxi023
M3 - Article
C2 - 15831576
AN - SCOPUS:26644454398
VL - 6
SP - 479
EP - 485
JO - Biostatistics
JF - Biostatistics
SN - 1465-4644
IS - 3
ER -