Sentences with phrase «multiple comparison test»

Data was analysed with a one - way ANOVA followed by the Bonferroni multiple comparison test (comparison of the different breed groups) or with an unpaired t - test (comparison of CM and CM / SM groups).

* p ≤ 0.05, ** p ≤ 0.01, *** p < 0.001, **** p < 0.0001 and non-significant (ns) p > 0.05 by Mann - Whitney test (A) and two - way ANOVA corrected for multiple comparison using Sidak's multiple comparison test (C).

Individual differences were studied by the Tukey's multiple comparison test.

One - way ANOVA was used for three - group comparisons, followed by post-hoc multiple comparison tests (as specified in figure legend).

Hyundai Tucson Perhaps validating the multiple comparison tests and strong ratings awarded by the motoring.com.au team, it's the Hyundai Tucson SUV that takes number - one place in this year's Top 10.

Not exact matches

The functional brain networks showed a clear small - world organization, expressed by λ ≈ 1 (c) and γ ≫ 1 (d) for T ≥ 0.3 (1 - sample t test, df = 18, all p < α of 0.01, Bonferroni corrected for multiple comparisons of T).

The functional brain networks showed a clear small - world organization for 0.3 ≤ T ≤ 0.5 (Fig. 1a — d), expressed by L ≈ Lrandom and λ ≈ 1 for T ≤ 0.5 and C ≫ Crandom and γ ≫ 1 for T ≥ 0.3 (one - sample t test, all p < α of 0.01, Bonferroni corrected for multiple comparisons of T, df = 18), indicating a small - world organization (Sporns et al., 2004; Stam, 2004; Achard et al., 2006; van den Heuvel et al., 2008b).

Statistical analyses were made using either Student's two - tailed unpaired t test or analysis of variance (ANOVA) as specified in the figure legends, and Newman - Keuls procedure was used for multiple comparison analysis.

Four independent (A versus B) group-wise comparisons were performed to identify differentially expressed genes: (i) iPSC versus hESC (1,952 Refseq - annotated genes were significantly enriched in iPSCs versus hESCs; 1,072 genes were enriched in hESCs versus iPSCs at P < 0.01 after correcting for multiple hypotheses testing); (ii) iPSC versus NSC (3,347 genes were significantly enriched in iPSCs versus NSCs; 2,959 genes were enriched in NSCs versus iPSCs); (iii) hESC versus NSC (2,376 genes were significantly enriched in hESCs versus NSCs; 2,541 genes were enriched in NSCs versus hESCs); (iv) iPSC and hESC versus NSC (3,730 genes were significantly enriched in iPSCs and hESCs, versus NSCs and 3,638 genes were enriched in NSCs versus iPSCs and hESCs (Tables S1 to S8 contain the full list of comparisons).

Comparisons involving multiple groups were evaluated using one - way or two - way ANOVA, followed by Tukey's post hoc test.

P - values from regression models were derived from the Wald test, and no adjustments were made for multiple comparisons.

This study evaluated a new set of cardiac patients for the primary outcome of diabetes, which was not significantly associated with fasting (after multiple - comparisons correction) in the first study (37) and, thus, required additional evaluation as the primary hypothesis test (38).

Ed - Data comparisons enable users to view test results for multiple schools or districts, along with other data, in one place.

Comparison: In particular if you're trying to evaluate how to best manage your investments, having multiple advisers can allow you to test drive a couple different approaches.

Climate modelers often consider information from well - established tests and comparisons among existing models to help decide on a new model version among multiple candidates.

Scientists are working their hardest to create the most accurate possible record of global temperatures, and use a number of methods including tests using synthetic data, side - by - side comparisons of different instruments, and analysis from multiple independent groups to ensure that their results are robust.

This discrepancy is probably due to the adjustments for multiple comparisons in the Tukey HSD test.

These non-significant results are arguably due to the study's relatively small sample size for a genome - wide association study that requires multiple testing (ranging from N = 372 — 436 in the high and low trait comparison groups), making it unclear whether the same genetic variants are involved in these sub-domains.

Individually significant coefficients were interpreted only if the equation in which they were estimated was significant as a whole in a multivariate test, an approach that minimizes the problem of false positives due to multiple comparisons while avoiding the problem of low power to detect true associations of moderate magnitude that is introduced by more conservative methods (eg, Bonferroni corrections).33 Model comparisons were made using the Akaike information criterion.34

This can also help us to alleviate concerns about multiple testing in the comparisons we report below.

All of the p values were calculated using a right tailed Fisher's exact test and corrected for multiple comparison with the Benjamini - Hochberg method.

In order to determine the extent to which this influenced the results of the MANOVA, results were re-evaluated using the «Kruskal — Wallis H» non-parametric comparison test for multiple independent samples.

This will involve both a small - sample comparison of complex EBP vs. simple EBT cases and within - subjects multiple baseline testing of the concordance of targeted changes with their matched practice elements.

The increase in Type - I error due to multiple statistical comparisons was controlled through the Simes correction procedure [47], a corrective method which offers a more powerful test than the classic Bonferroni - correction.

In an adjustment for multiple comparisons the corrected p - value was 0.0015, indicating that 21 of the 25 statistically significant comparisons remained significant in the final Poisson model testing for susceptibility (Table 3).

Finally, despite the use of complementary statistical methods and high statistical power, corrections for multiple comparisons indicated that 21 of the 25 statistically significant comparisons remained significant in the final Poisson model testing for susceptibility.

Unadjusted group differences were tested by using analysis of variance with Bonferroni posthoc tests (to adjust for multiple comparisons) for continuous variables and the χ2 test for categorical variables.