Sentences with phrase «for multiple comparisons»

Throughout, Q values indicate significance of differences after adjusting for multiple comparisons by controlling the false discovery rate for selected comparisons.

All differences reported are significant at the 0.05 level with appropriate adjustments for multiple comparisons.

The number of symptoms and vitamin D levels had a borderline significant relationship at first, but after the analysts adjusted for multiple comparisons, the association disappeared.

* 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).

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.

All analyses were also performed using Bonferroni corrections; we present results from analyses in which no corrections were made for multiple comparisons since the findings were consistent.

The odds of type 2 diabetes were not statistically significant after adjustment for multiple comparisons among the second generation, but co-corresponding author Dr. Sun Changhao, professor of nutrition and dean of the School of Public Health at Harbin, noted that these people were only in their 20s and 30s and could still be at increased risk as they age and that the research team will continue to follow up on these participants.

Statistical significance was determined via one - way ANOVA with the Newman - Keuls procedure for multiple comparison analysis.

We then conducted multivariate (logistic) regression analyses to test the overall statistical significance of the complete set of psychosocial variables (thus controlling for multiple comparisons).

According to the Bonferroni method, the significance level α was set to 0.025 to account for multiple comparisons.

For the in vivo experiment, two - way ANOVA corrected for multiple comparisons using Sidek's multiple comparison test was used.

Finally, we conducted a post hoc analysis to adjust for multiple comparisons using the Bonferroni correction and a sensitivity analysis to determine the effect of potential unmeasured confounders.

We employed false discovery rate (FDR) correction to correct for multiple comparisons across brain regions.

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

Bivariate correlation coefficients are presented, with uncorrected p values for multiple comparisons.

A false discovery rate (FDR) correction was used to control for multiple comparisons.

Examining all the combinations of smoking status of parents and grandparents with the gender of the children and four different traits is quite likely to generate a chance finding of borderline significance, especially when using a series of different adjustments and not adjusting for multiple comparisons.

For multiple comparisons, one - way ANOVA was applied, then pair-wise comparison was performed by Tukey - Kramer (Figs 1H, 4D and 5E and 5F) or Dunnett test (Fig 1I).

For multiple comparisons, one - way ANOVA with Tukey's post hoc analysis was used.

There was a suggestion of increased ASD risk among children whose mothers received an influenza vaccination in their first trimester, but the association was not statistically significant after adjusting for multiple comparisons, indicating that the finding could be due to chance.