Sentence examples for bootstrap techniques for the from inspiring English sources

The statistical simulation procedures involve permutation tests and bootstrap techniques for the construction of confidence intervals for the difference of measures.

In this paper the application areas of simulation in the CNS/ATM context are reviewed together with the simulation methods that can help solve the main problems encountered, i.e. quick simulation techniques for the simulation of rare events, and the bootstrap technique for the evaluation of the accuracy of the results.

We compare two methods, which can handle the aforementioned issues, in addition to the standard unadjusted bootstrap techniques for assessing cost-effectiveness in the Helsinki Psychotherapy Study based on five repeated measurements of the Global Severity Index (SCL-90-GSI) and direct costs during one year of follow-up in two groups defined by the Defence Style Questionnaire (DSQ) at baseline.

We used a cluster bootstrapping technique for the calculation of 95% confidence intervals (95% CI) [ 18]. 2. We used the generalized estimating equations (GEE) approach to fit logistic regression models [ 19] for evaluation and comparison of SAR between intervention groups.

We can find in literature various applications of bootstrap technique for example to assess the stability of the cell lines cluster dendrogram in unsupervised microarray analysis [ 42].

E[ p] is the expected value of p using the bootstrap technique for 100 000 bootstraps.

We developed and tested a methodology combining MI with bootstrapping techniques for studying prognostic variable selection.

Finally, though we were not able to validate our models externally, we used the bootstrapping technique for validation that is considered as the preferred method for internal validation [ 40].

We used the bootstrap resampling technique for the unbiased evaluation of classifiers for each feature set.

On the basis of the present analysis using the bootstrap technique, the medical team must have sufficient information to choose the best scoring system for the clinical context.

The two tests demonstrate that the bootstrap technique may be the optimal approach for non-ideal dataset.