“highly significant”

Analyses of tumour characteristics by year of diagnosis showed a significant trend towards lower risk tumours in more recent years, driven by a highly significant trend towards lower nodal status (p<0·0001 for both oestrogen receptor-positive and oestrogen receptor-negative groups; table 1 ; appendix p 35 ).

Results We observed a highly significant correlation between the storage time of pRBC units and a drop in pH, as well as an increase in potassium and lactate of stored red cells ( p < 0.0001).

Statistical analyses revealed that this elevation was small (14.5 μg/g) but highly significant ( p -value < 0.0001).

It is also plausible that these inconsistent results are due to the relatively small sample size in MRI studies, as a related clinical study from TREND with a much larger sample size ( N = 661) revealed a highly significant and slightly stronger correlation between TMT B-A and DT gait speed while subtracting ( p < 0.0001, r = 0.27) ( Hobert et al., 2017 ).

Geographical Differences in Skull Shape, Diversity and Size Highly significant shape differences ( p < 0.0001) were detected among all areas, except between Arctic localities (High Arctic vs.

This model was highly significant ( P < 0.0001), although it only explains a small fraction of the variance (Nagelkerke r 2 = 0.04).

Total glutathione was decreased by about a factor of two in both mutants and controls exposed to galactose plus paraquat as compared with galactose alone; this difference was highly significant ( P <0.0001; Fig. 6A ).

No significant differences in the prognostic value are noted between iPET-2 and i-PET-4 with both showing highly significant differences in EFS between the CMR and nCMR patients ( P -value < 0.0001): patients with iPET-2-CMR and iPET-2-nCMR had 3-y-EFS’s of 93.1% and 45.5%, respectively while the respective values for patients with iPET-4-CMR and iPET-4-nCMR were 89.5 and 39.4%.

The fitted exponential decay models were all highly significant (r 2 > 0.74, p < 0.0001; Fig. 5 ) with decay constants (r) differing significantly between single-species (chironomid only) and multispecies (two and three species) treatments.

Due to the large number of variables, non-parametric tests were consistently used and a statement regarding statistical significance was only made in the case of highly significant p-values ( p ≤ 0.0001).

Survival analysis showed that the age-specific survival rate curves ( l x ) of the population under different irradiation doses had highly significant differences ( χ 2 = 904.655, df = 6, p < 0.0001), and there was a significant linear trend ( χ 2 = 697.500, df = 1, p < 0.0001) ( Figure 3 ).

Statistical analysis revealed that this difference was highly significant (p < 0.0001).

Indeed, a comparison between the times of peaks and troughs of conidiation showed large differences between these phase markers in a Δ frq strain, and a detailed statistical analysis (paired t -test) for peaks and troughs of conidiation confirmed that these differences are, with one exception, highly significant (paired t -test, P < 0.0001; see Table S2 for t - and P -values for all phase markers, T cycles, and strains analyzed).

This analysis confirmed highly significant effects of both treatment (χ 2 = 158.84, p < 0.0001) and time (χ 2 = 43.82, p < 0.0001) on germination.

In Table 3 , regular alcohol consumption by the spouse was found to have a highly significant association with both psychological violence (p = 0.0001) and physical violence (p = 0.0008).

The postoperative volumes in the placebo and nucleoplasty groups were 1.078 ml (SD: 0.350 ml) and 0.906 ml (SD: 0.287 ml) respectively; the difference is highly significant (p<0.0001) ( Fig. 4 ).

Natural Sciences and Engineering Research Council of Canada 10.13039/501100000038 RGPIN‐2023‐03515 Highly significant differences in WEP were observed among soils ( p < 0.0001) and treatments ( p < 0.0001) with a highly significant soil × treatment interaction ( p < 0.0001).

Differences were considered as ‘not significant’ in cases with p-values > 0.1, as ‘borderline significant’ ( # ) with p-values between 0.05 and 0.1, as ‘significant’ (*) with p values between 0.01 and 0.05, as ‘highly significant’ (**) with p values between 0.001 and 0.01, as ‘very highly significant’ (***) with p values between 0.0001 and 0.001 and as ‘extremely significant’ (****) with p-values < 0.0001.

The second-order polynomial equation derived from the experimental data was: Y = 38.16 + 0.6625 A – 0.3875B - 0.5250C + 0.2000AB - 0.3750 AC + 0.6250 BCE - 3.73A 2 –1.33B 2 –1.50C 2 The ANOVA results ( Table 4 ) demonstrated that the regression model was highly significant ( p < 0.0001) with an F-value of 60.87.

1 e) and found a highly significant correlation (Spearman's r = 0.57 [95% confidence interval (CI): 0.54–0.60], p < 0.0001).

Bartlett's test of sphericity was highly significant ( P < 0.0001), indicating good model acceptability.

All inter-device correlations elicited a highly significant correlation with r-values of 0.72–0.86 (all p < 0.0001, Table 2 , Supplemental Figure S4).

Simultaneously, the results from Table 2 reveal that the individual factors A and D exert a highly significant influence on the response value ( p < 0.0001), while factors B and C exhibit a significant impact ( p < 0.05).

Heterogeneity was substantial ( I 2 = 97.6%, 95% CI: 96.8%–98.2%), with a highly significant test for heterogeneity ( Q [10] = 423.48, p < 0.0001).

The U-JVP Ruler technique was only able to produce a moderate correlation with CVP, although their relationship remained highly significant ( r = 0.63, 95% CI 0.6059–0.7978, p < 0.0001) (Fig. 3 b).