Sentence examples for correction for multiple sampling from inspiring English sources

Comparisons between means were performed using one-tailed Student's t-test for paired data with Bonferroni correction for multiple sampling as appropriate.

This involved linear modeling for each gene, use of an empirical Bayes method to moderate the standard errors of the estimated log-fold changes, and correction for multiple sampling using the method of Benjamani and Hochberg [ 34].

Pair-wise comparison analyses of near-triploid (n = 22) versus near-diploid/tetraploid (n = 27) NBTs revealed small sets of differentially expressed genes when using a stringent correction for multiple sampling, (6 genes [FDR < 0.01] and 12 genes [SDP < 0.1]) (see Additional file 2).

These were: (1) genes with a more than twofold difference in mean expression between control and exposed samples; (2) genes with significantly different (p < 0.05) expression between control and exposed samples after correction for multiple sample testing [ 56].

Statistical analysis was performed with Stata 9.1 for Windows (StataCorp LP, College Station, TX, USA), by using one-way analysis-of-variance model with Bonferroni multiple-comparison correction for multiple sample experiments and the Mann–Whitney test for experiments with comparison between two groups.

Corrections for multiple sampling (Bonferroni method and Dunnett's multiple comparison test) were used where appropriate.

Since it is not statistically valid to test multiple divisions with corrections for multiple sampling, rigorous statistical evaluation is achieved by defining divisions in a training set and then validating them in an independent non-overlapping validation set.

The fact that the DAVID pathway enrichment analysis system itself includes an algorithm for multiple sample correction effectively limits type 1 errors during identification of enriched pathways.

Further, the potential for type I error in identifying overrepresented pathways is also controlled for by the fact that the Database for Annotation, Visualization and Integrated Discovery (DAVID) tool that was used for enrichment analysis itself includes an algorithm for multiple sample correction.

Above all, despite the correction for multiple comparisons, the small sample size raises the possibility of Type I error.

Statistical analysis was performed using the Wilcoxon test followed by Bonferroni correction for multiple comparisons of paired samples for the synovial biopsy data.