“highly significant”

Dropping out and psychological consultation due to burnout showed highly significant associations with all burnout dimensions (p < 0.0001).

The correlation between the observed and expected gene expression ratios as calculated by bivariate analysis was statistically highly significant with the Pearson correlation coefficient being 0.93 and p -value < 0.0001 (Fig. 3 ).

The difference in RWL between the 2 groups was highly significant (T-test: p<0.0001).

For all heat strain variables, the splines te(T a , p a ) modeling the influence of temperature and humidity were statistically highly significant ( p < 0.0001).

This was a highly significant ( P < 0.0001) difference.

Concerning attention behavior during familiarization, a repeated-measures ANOVA with looking time as dependent measure, language group (Catalan, Spanish, bilingual) and familiarization condition (TB or GM) as a between-group factors and trial (first, last) as repeated measures revealed a highly significant effect of familiarization trial [ F (1, 48) = 42.9; p = 0.0001; η 2 = 0.47], and no effect of language group or condition and no significant interactions [familiarization trial × language group: F (2, 48) = 1.15; p = 0.32; η 2 = 0.04; familiarization trial × condition: F (1, 48) = 1.7; p = 0.19; η 2 = 0.03; familiarization trial × language group × condition: F < 1].

The effects on tumor growth between the experimental groups were highly significant: shRNA ctrl versus shRNA UNG ( P < 0.0001), shRNA ctrl plus FdU treatment versus shRNA UNG ( P = 0.003), and shRNA ctrl plus FdU versus shRNA UNG plus FdU ( P = 0.003).

For the primary variable GIS the difference between placebo and verum after 28 days of treatment showed a highly significant (p < 0.0001) difference between placebo and verum (6.7 resp. 4.7 points).

The relationship between catalyst loading and reaction time is highly significant ( F -value = 27.59, p < 0.0001), pointing out that optimization of both parameters is required for an optimal yield ( Table ).

The interaction term for eGFR and urine ACR was highly significant ( P <0.0001, multiplicative interaction term), indicating that eGFR significantly modified the association between urine ACR and incident AF (Table 2 ).

A one-way analysis of variance (ANOVA) confirmed a highly significant correlation between group classification and cockroach length ( P < 0.0001), confirming the procedure performed to classify cockroaches into groups.

The difference between the treatment groups was highly significant ( P < 0.0001).

We found highly significant differences in haplotype distribution between patient and control groups both in the original sample and in the replicated sample (global p < 0.0001 after multiple test correction).

The age difference between the two scan angle groups was highly significant (Mann–Whitney U test, p < 0.0001).

A highly significant association between strong CENPF expression and early PSA recurrence was seen in all tumors ( p <0.0001, Figure 6A ) and in the subset of ERG fusion-negative cancers ( p <0.0001, Figure 6B ).

This difference was highly significant (Chi-square df 2 = 18.1, p < 0.0001).

A highly significant correlation (R > 0.83, p < 0.0001) was found between the fractional stability parameters of the different state space reconstruction methods (i.e., Equations 4–6) indicating robustness of the parameters to the choice of state space reconstruction method.

melliferum populations were more stable year to year ( P = 0.0544) but showed highly significant seasonal variation ( P < 0.0001).

Total facility time was reduced by 48 min and costs were 39.35% lower in the ES group, with all comparisons showing highly significant differences ( p < 0.0001). cost analysis drug‐induced sleep endoscopy hypoglossal nerve stimulation obstructive sleep apnea procedure efficiency 2.5 Discussion Drug‐induced sleep endoscopy can be efficiently and safely performed in the endoscopy suite in a cost‐effective manner.

Results ANOVA showed a highly significant effect of time in all the horses for the vitamins studied ( p < 0.0001).

All these differences were highly significant (pairwise two-tailed t-tests, P<0.0001).

One-way ANOVA for repeated measurements confirmed a highly significant difference between baseline and follow-up within both treatment groups (P < .0001).

All of the interactions are highly significant ( p < 0.0001).

The association between mortality and socioeconomic patterns was highly significant ( p -value <0.0001).

Second, a linear regression of perch temperature over mean environmental temperature is highly significant ( P < 0.0001) and the slope of 0.897 is significantly different from a slope of 1 ( t = −3.233, df = 177; P < 0.005).