“highly significant”

This difference in response between the two species was reflected in the P-application rate × species interaction being highly significant (two-way ANOVA, F 3, 24 = 9.34, P < 0.001), but the main effect of P application being non-significant (two-way ANOVA, F 3, 24 = 1.91, P = 0.154).

The baseline AAAS score was also highly significant, with every point higher on the baseline AAAS predicting a 0.48 higher AAAS score at follow-up (beta = 0.48; SE = 0.09; P < 0.001).

The booster vaccination resulted in a highly significant (P < .001) GMT increase to 461.7 (95% CI, 295.4–721.8) at 3 weeks postbooster (Figure 2 B), with an 11.6-fold increase in GMT compared with baseline.

Galling Insect Richness x Tree Species x Forest Type Our initial (maximal) model was highly significant (d.f. = 36,41; P<0.001) and explained 83% of variability observed in the galling insect richness (GIR).

Model analysis demonstrated a highly significant time effect across all models (all P < 0.001), indicating a marked increase in B-line scores over time.

Analysis of variance revealed that temperature (A), catalyst loading (D), and the methanol-to-oil ratio (C) were highly significant ( p < 0.001), whereas reaction time (B) showed moderate significance ( p = 0.0645).

Because the 95% confidence interval is relatively narrow for this effect and does not include 0, these findings can be interpreted as a medium summary effect that is positive, precise, and highly significant ( p < 0.001).

As a consequence, performance in Experiment 1.2 was worse near the lateral wall than along the corridor's midline: In contrast to Experiment 1.1, there was a highly significant main effect of lateral wall distance in Experiment 1.2 (F 1,30 = 32.38, p<0.001).

The overall improvement in model fit was highly significant (nested chi-square = 99.92, df = 6, p <.001).

The PC group found searching easier (2.78) than those students who used a smartphone (1.77), and this difference was highly significant ( P < .001).

Benthic biomass was inferred from flux at 500 m above the seabed [poc.flx.mean = POC flux at 500 m above seafloor (mg C m −2 day −1 )] using a previously published highly significant statistical relationship ( P < 0.001) between a large spatially referenced database of benthic biomasses (mg C m −2 ) of meiofauna (mei.biom), macrofauna (mac.biom), and megafauna (meg.biom) and POC flux at 500 m above seafloor estimated from satellite data ( Wei et al. , 2010 ).

Among them, the social value shows a highly significant positive effect (β = 0.520, p < 0.001), followed by the economic value (β = 0.486, p < 0.001).

There was a highly significant ( P <0.001) positive Pearson correlation of LVSV measurements by EV and TTE for the whole cohort (EVVTI, r = 0.934; EVMM, r = 0.896) and for subgroup analyses for OTX subgroup (EVVTI, r = 0.929; EVMM, r = 0.869), SEPSIS subgroup (EVVTI, r = 0.911; EVMM, r = 0.863) NEURO subgroup (EVVTI, r = 0.955; EVMM, r = 0.899), and PREM subgroup (EVVTI, r = 0.786; EVMM, r = 0.728).

Additionally, severe ADL dependency was observed in 75.9% of participants before the intervention, which dropped significantly to 9.3% afterward, also showing a highly significant difference ( p < 0.001).

3 Results 3.1 Differential effects of lighting and species on growth and chlorophyll traits Two-way ANOVA revealed ( Table 2 ) that both lighting (p < 0.05) and species (p < 0.001) had highly significant effects on SFW, with a strong interaction also observed between these factors (p < 0.001).

Additionally, a highly significant inverse correlation was found between preoperative AV annular diameter and peak AV gradient at follow-up ( P < .001), as well as a significant inverse correlation between preoperative AV annular diameter and IVC at follow-up ( P = .022) ( Figure 7 ).

Sampling location, time, operator and sex effect The effect of sampling location in the site locations around the same pond was highly significant (P < 0.001) for all traits studied, including body colour of both raw and cooked shrimp (Figures 2 and 3 ).

A highly significant likelihood-ratio test ( χ 2 = 29,231, df = 3, p < 0.001) confirms that the random-effects (RE) specification fits the data far better than a fixed-effects (FE) approach, validating the choice to model heterogeneity explicitly.

In contrast, species differences in the proportion of aphids that fell from the host plant as a result of chill coma were highly significant (χ 2 2 = 20.80 p<0.001), with significantly more M. dirhodum falling from the plant as a result of chill coma, and significantly less R. padi than expected (relative proportions for M. dirhodum , R. padi and S. avenae are 0.45, 0.02 and 0.21 respectively).

Although the association of eGFR with LDL-C lost significance after further adjustment, the associations of eGFR with apoC-III remained highly significant in the fully adjusted model that also accounts for urinary ACR (p = 0.001).

After correction, the association between ARSSS and baseline viral load remained highly significant (p<0.001).

The Kaiser-Meyer-Olkin (KMO) value was 0.911, and the Bartlett’s test of sphericity was highly significant ( p < 0.001), indicating a high degree of correlation among the variables.

Both showed highly significant negative correlations [ r = −0.664, t (22) = 4.16, p < 0.001 with the s values and r = −0.926, t (22) = 11.52, p < 0.001 with the l values], which was consistent with the chromatic diffusion.

Statistical significance testing across 1000 test images confirms highly significant improvements ( p < 0.001) with large effect sizes, while ablation studies validate the requirement of each model component.

When correlations between scores of items 2, 3 and 4 and self-esteem level were examined, a highly significant correlation ( P < 0.001) was found between items 2, 3 and 4.