“highly significant”

mutans count during the 4-week period which was of highly significant value, F (1.664, 34.000) = 169.607, P = 0.000.

In the CS group, a statistically highly significant mean difference for postinjection VAS and SEM scores between the conventional and CS techniques was observed, which was 2.160 ( p = 0.000) and 2.760 ( p = 0.000), respectively.

Logistic regression showed a highly significant result (Wald statistic = 12.3, df = 1, and P < 0.000), with the following classification parameters: sensitivity = 94.7% and specificity = 86.8%; that is, 94.7% and 86.8% of patients and controls, respectively, were classified correctly.

A highly significant association was found between the oral hygiene and socioeconomic status (p=0.000).

This difference was found to be highly significant (P = 0.000).

We also found a highly significant correlation of the general sense of coherence between T0 and T1 for the experimental group ( r = 0.885; p = 0.000).

There was a highly significant correlation between the extracted volume of urine and the amount of ng/tube (r = 0.979, n = 17, p <0.000).

However, the association between ACE/ARB use and COVID-19 infection remained highly significant after adjusting for the propensity score and these variables (OR 0.65, 95% CI 0.48–0.87, p = 0.00) ( S3 Table ).

The likelihood ratio statistics (LR chi-square (60) = 356.33) are highly significant P < 0.0000).

When compared within the groups, statistically highly significant reduction in clinical parameters such as PI, SBI, PPD, and CAL was observed for each treatment modality with P < 0.000.

The comparison of the SKT profiles between the three diagnostic groups included in the study across all nine subtests revealed a highly significant interaction effect ‘diagnosis × subtest’ (Pillai’s Trace = 0.121 with F (16, 1080) = 4.34, p < 0.000) in a multivariate analysis of variance with repeated measures (MANOVA), which indicates an overall difference of test profiles.

On applying chi-square test between blood group and Decayed, Missing and Filled Teeth (DMFT) score, a highly significant association (p=0.00) was observed.

This increase was highly significant in both tissues in diabetic rats and diabetic rats treated with HgCl 2 compared to the sham group (P = 0.000).

The moderation analysis showed that PDs with a non-traditional format have a highly significant effect on self-efficacy ( g = 0.820, p = 0.000) and PDs with a traditional format have a modestly significant effect on self-efficacy ( g = 0.462, p = 0.000).

The impact of the intervention on patient knowledge was highly significant (mean difference = 17.7%, 95% confidence interval (CI) = 21.75–13.58, P < 0.000).

The PHQ9 depression score was higher in sleepy subjects with SES ≥ 11 compared to non-sleepless subjects; the difference being very highly significant (PHQ9=11.97 ± 4.99 and 6.54 ± 5.27 respectively; p=0.0000).

Chi-square testing revealed a highly significant effect of WL on crack formation at WL and 1 mm short of WL (p = 0.000).

Results The results of statistical analysis and structural equation modeling (SEM) indicated that teachers’ immediacy behaviors (verbal, nonverbal) had a highly significant influence on EFL students’ WTC (ß=0.89, p = .000) and academic engagement (ß=0.71, p = .000).

Association Between Fasting C-Peptide Levels and Severity Scores of Femoropopliteal Arteriosclerosis ( Table 3 ) According to the Fontaine score, there was a highly significant increase in fasting C-peptide levels in patients with a IIB score compared to those with an IIA score (p=0.000).

However, there is a statistically highly significant difference when comparing Group III with Group I and Group II with P < 0.000 and < 0.001, respectively [ Table 1 ].

In this study, the biomass regression model ( Table 5 ) was highly significant ( F =35.12; P =0.000) with an adjusted R 2 of 94.29%, indicating that only 5.71% of the variability in the response is not explainable by the model.

The hypothesis test demonstrated a highly significant relationship between awareness of consequences and attitude (H4) ( t = 8.164, p = 0).

Conversely, two factors demonstrated a highly significant influence: Use of a Transepithelial Abutment: This variable showed a profoundly significant association with bone loss (Chi-square, p=0.000).

4.2 Linear regression analysis The provided regression results in Table 3 reveal that the effects of instructor readiness dominated the other readiness elements, as this predictor was highly significant (P-value = 0).

The inverse Simpson index also revealed a highly significant difference between sample types (Kruskal-Wallis H = 12.86, p = 0), with hosts demonstrating greater community diversity compared to ticks.