“highly significant”

Most interestingly, we found a highly significant interaction between group membership and SCC on measures of perceived cognitive abilities – CogPCA [ F (1) = 14.84, p < 0.001, η 2 = 0.05], cognitive functionality on quality of life - CogQoL [ F (1) = 9.90, p < 0.01, η 2 = 0.04], and cognitive difficulties referred by others – CogOTH [ F (1) = 21.95, p < 0.01, η 2 = 0.03].

The calculated value of t = 14.548 and t = 8.601 was statistically highly significant at a p < .001 level ( Table 3 ).

In model 4, the autoregression term was highly significant (OR, 1.18, p<0.001).

Regression analysis showed a highly significant effect ( P < 0.001) considering the body weight of each mouse, using the CalR platform and analysis of covariance (ANCOVA) statistical analyses 37 .

However, although this correlation is weak, it is highly significant ( p < 0.001).

A result was considered significant if p < 0.05, highly significant if p < 0.01, and extremely significant if p < 0.001, according to the previous studies. 3.

The interaction effect of the gain or loss situation and childhood SES was highly significant, F (1, 105) = 20.54, p < 0.001, η 2 = 0.16; see Figure 1 .

The results of analysis of variance show a very highly significant difference in the total aerobic mesophilic flora (TAMF) from one Gbeli sample to another ( p < 0.001).

oryzae evidenced highly significant differences in mortality of the adults (χ 2 = 165.81; df = 4; p < 0.001), with survival rates of the individuals treated with S. bocconei EOs from stems or leaves similar to the ones treated with pyrethrum ( Figure 1 A).

The model was highly significant ( p < 0.001).

Highly significant differences ( p < 0.001) were observed among the means of accessions for the other 40 Tomato Analyzer descriptors and two conventional traits ( Table 1 ).

Statistical analysis showed a highly significant correlation ( p < 0.001), which confirmed the gradual decline in the number of tracheal intubations used in favour of more frequent use of SAD.

autism spectrum disorder phenotypic analysis multivariate statistics classification diagnostic National Institutes of Health 10.13039/100000002 R01 MH1000281 5TR01MH117982 Simons Foundation 10.13039/100000893 95489 A multivariate analysis of variance was conducted on the data to confirm the significance of the results of the LDA; the results of this analysis indicated highly significant results (Wilks’ lambda = 0.13065, F(105, 1025) = 9.501, p < 0.001).

We collapsed the estimates of “allelic richness” and “alleles per locus” as reported in CaliPopGen into one metric because they are highly correlated: comparing data for 174 populations that had both metrics available returned a strongly positive association that was highly significant (Pearson’s correlation r = 0.894, df = 173, P < 0.001).

We found that the DE pathways involved in cell cytotoxicity, such natural killer cell-mediated cytotoxicity, spliceosome and proteasome pathways, were highly significant ( P < 0.001) for the discordant cell Clusters 3 and 4.

4a,b ), a difference that is highly significant ( P < 0.001).

Among the enriched metabolic pathways, three, namely, starch and sucrose metabolism, plant hormone signal transduction, and flavonoid biosynthesis, reached a highly significant level of enrichment (P < 0.001) ( Table S6 and Figure S3 ).

Moreover, a highly significant model ( p < 0.001, Table 3 ) and insignificant loss of fit ( p = 0.0995, 0.8433, and 0.6377 for TPC, ABTS and FRAP, respectively) were observed.

The Kruskal–Wallis test, on the other hand, showed highly significant ( P < 0.001) CN variation of all genes across breeds, with a slightly lower significance ( P = 0.003) for HSFY ( Table 2 ).

When we assessed the impact of the intervention on different weaning practices indicators among participants, the outcome of interest was the remarkable increase in the percentage of our targeted objectives, exceeding our expectations with highly significant difference between pre- and post-interventional village and between post-interventional and control villages ( P = 0.001).

Spearman correlations ( Table S1 in the Supplement) revealed highly significant positive relationships between all WMH measures (0.36 ≤ r s ≤ 0.89; all p < 0.001).

Highly significant differences in microbiome diversity were detected using ANOSIM pair-wise comparisons between all species (ANOSIM R ≥ 0.95, p = 0.001), while location differences produced lower dissimilarities (R < 0.04).

Unlike in children, total injury severity and injury severity with an ISS ≥16 also had highly significant influences on intubation (ISS ≥16: odds ratio 1.5, 95% CI: 1.4–1.7; p < 0.001).

Both the pre- and postintervention comparisons of the simultaneous use of ≥4 antibiotics between units by type of hospital were highly significant ( P = .001 for both).

It also revealed three PCs with highly significant differences (p<0.001) and the first three interaction principal component of AMMI, explaining 47%, 26.62%, and 17.88% of the GEI with 19, 17, and 15 degrees of freedom (df), respectively, as well as the fourth PC with significant differences (p<0.05) explaining 7.77% of the interaction with the degree with total cumulative of nearly 100%.