Excerpts

Assessment of goodness of fit indicated that the overall model was highly significant ( p < 0.001, adjusted R 2 = 0.334).

Also, the mobility reduction following the lockdown measures were found to be highly significant ( p < 0.001) through all stratifications considered (age, gender, and region).

ASC also showed a highly significant adjusted difference between the groups after adjustment of duration of diabetes as a covariate (Wald χ2=29.810, p < 0.001*) (Table 4 ).

Carbachol treatment resulted in a highly significant depression of field EPSP responses ( t (16) = 6.60, P < 0.001).

The pollutants included in the redundancy analyses (RDA) explained 62% of the variation of the biomarkers of energy metabolism, and the RDA model was highly significant based on Monte-Carlo test (1000 replicates, RV coefficient = 0.49, p < 0.001).

There was a significant trend of decreasing risk with increasing number of live births (P=0.001), and women remaining nulliparous after treatment completion conferred the highest risk (standardised incidence ratio 1.57 (1.37 to 1.79); table 3 ).

All three were highly significant independent predictors ( P < 0.001 for each) (Table 4 ).

However, the temporal patterns of total epizootics ( Fig 2A ) and human cases ( Fig 2D ) (based on data from the Ministry of Health) and the YFV infection in NHP studied here were roughly equivalent ( Fig 2B ), and the temporal smooth was both highly significant (P<0.001; Table 2 ) and accounted for a large proportion of the model deviance (R = 0.54 and R = 0.22; Table 3 ).

Seedling morphometrics In 2005, distance had a highly significant effect on number of leaves per seedling, with more leaves per seedling away (7.6±0.3 leaves) than close (6.2±0.2; F 1, 97 = 12.54, P <0.001).

The continuous variables (altitude and snow) are both highly significant ( p < 0.001), although with values of different signs.

The mean score was 19.29±9.62 for the subjects over 65 years, showing a statistically highly significant result ( P <0.001).

The immediate reductions in transmissibility accounting for the effect of PHSMs were highly significant (p values <0·001) and with estimated reductions ranging from 17% (95% CI 13 to 21) to 41% (35 to 46) across the locations and countries, with comparatively higher reductions for Hong Kong and Italy, for which the COVID-19 PHSMs were implemented just before or around the expected seasonal peak ( figure 2 , table , appendix 1 p 21 ).

Two-proportion Z tests revealed that the differences in proportions of populations in the EHR-vs registry-derived datasets were highly significant for all cohorts ( P < .001) ( Table 1 C). 3.2 Cohort modelling The EHR- and registry-derived data were used to calculate the predicted proportion, and statistically representative range, for each demographic cohort for hypothetical US SLE trials of 100 subjects and 300 subjects.

Estradiol concentrations identified highly significant differences among the three groups ( p < 0.001) ( Table 1 ).

We recorded a highly significant effect of the inclination of the path on the probability of rolling upon perceiving the stimulus (Logistic Regression Model, rubbing: χ 2 1,10 = 752.3, P < 0.001; tapping: χ 2 1,10 = 767.3, P < 0.001, n = 60 for each angle of each treatment).

This upward shift continued, with women comprising 37% of speakers (38/103) by 2024. By domain, plenary sessions showed a significant trend ( P < 0.001).

The analyses of co-variance revealed a highly significant effect of group ( F 1,50 = 44.23; p < 0.001] with a large effect size (partial η 2 = 0.47) and high power (1− β > 0.99) given the sample size of the analysis.

For visual fatigue, the effect of condition was highly significant ( F (2, 22) = 29.87, p < 0.001).

This increase was highly significant with large effect sizes for all domains, ranging from “(b) pharmacological treatment of ADHD” ( F (1, 287) = 475.48, p < .001, partial η 2 = 0.62) to “(a) psychopathological assessment” ( F (1, 283) = 1250.75, p < .001, partial η 2 = 0.82).

2024 ) (Table S8 ), showed highly significant positive correlations (FDR‐adjusted *** p < 0.001) with all 10 patient‐level disease risk scores examined (bowel cancer, COPD, depression, diabetes, IBD, IHD, lung cancer, pain, RA, and stroke).

For deep invasion, the AUC was 0.649 for T2WI, 0.906 for T2WI + DWI, and 0.906 for T2WI + DCE-MRI (Tables 4 , 5 ) The chi-square test revealed a highly significant association between the MRI findings and the histopathological stage for T2WI (χ2 = 28.666, p = 0.001), T2WI + DWI (χ2 = 66.696, p = 0.0005), and T2WI + DCE-MRI (χ2 = 78.186, p = 0.0005) (Tables 6 - 8 ).

Highly significant ( p < 0.001) increases in mortality were observed in individuals with cardiovascular disease, hypertension, cancer, diabetes, and hyperlipidemia, but not with obesity, thyroid disease, or respiratory disease.

Results The results of our global panel regression analysis showed that there was a highly significant correlation between prevalence and mortality (ρ=0.8304; P <.001).

Interestingly, Matsuo and colleagues had found that Jax mice emitted 16–25% more DSI contacts than NIH mice, a difference that became highly significant ( P <0.001) if the group sizes exceeded 10.

Adding to my surprise, Table 1 of Appendix 1 showed a highly significant association of depression (p< 0.001) across three latent profile groups.