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Bias and variance reduction in nonparametric estimation of time-dependent accuracy measures
- Source :
- Statistics in Medicine. 35:5247-5266
- Publication Year :
- 2016
- Publisher :
- Wiley, 2016.
-
Abstract
- A new nonparametric approach is developed to estimate the time-dependent accuracy measure curves, which are defined on the cumulative cases and dynamic controls, for censored survival data. Based on an estimable survival process, the main intention of this study is to reduce the finite-sample biases of nearest neighbor estimators. The asymptotic variances of some retrospective accuracy measure estimators are further reduced by applying a smoothing technique to the underlying process of a marker. Meanwhile, practically feasible and theoretically valid procedures are proposed for bandwidth selection in the presented estimators. In addition, the proposed methodology can be reasonably extended to accommodate stratified survival data and survival data with multiple markers. As shown in the simulations, our new estimators outperform the nearest neighbor and inverse censoring weighted estimators. Data from the AIDS Clinical Trials Group study 175 and an angiographic coronary artery disease study are also used to illustrate the proposed methodology. Copyright © 2016 John Wiley & Sons, Ltd.
- Subjects :
- Statistics and Probability
Epidemiology
Nonparametric statistics
Estimator
U-statistic
01 natural sciences
k-nearest neighbors algorithm
010104 statistics & probability
03 medical and health sciences
symbols.namesake
0302 clinical medicine
Censoring (clinical trials)
Statistics
symbols
Econometrics
Variance reduction
030212 general & internal medicine
0101 mathematics
Gaussian process
Smoothing
Mathematics
Subjects
Details
- ISSN :
- 02776715
- Volume :
- 35
- Database :
- OpenAIRE
- Journal :
- Statistics in Medicine
- Accession number :
- edsair.doi...........78e03b50116b033b1531c1489ddcc831