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Kaplan-Meier methods for clustered data estimated symptom-free survival time.
His research interests include the design of CRTs and analysis methods for clustered data, among many other interests.
For the adjusted analysis we will perform regression analysis of individual level data using methods for clustered data, multilevel, hierarchical or random effects models [ 37, 43].
Since the unit of randomisation is the PHCC, we will use a regression analysis of individual level data using methods for clustered data [ 38].
The small sample size and number of events in some participating centres is a limitation in our analysis because we modelled the mortality using methods for clustered data with centres as clusters.
There is already a rich class of bootstrap methods for clustered data in the literature but there is an absence of detailed theoretical results on the properties of these methods [ 39].
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Evolutionary Monte Carlo Methods for Clustering.
Nevertheless, existing methods for clustering XML documents are designed to work in a centralized way.
Experiments on artificial and real data sets show that HDDC outperforms existing methods for clustering high-dimensional data.
Accordingly, we use Expectation Maximization (EM), Principal Component Analysis (PCA) and Adaptive Neuro-Fuzzy Inference System (ANFIS) methods for clustering, noise removal and prediction tasks, respectively.
A variety of methods for clustering photographs have been proposed [12, 13].
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CEO of Professional Science Editing for Scientists @ prosciediting.com