There was a highly significant difference in median percentage weight loss both amongst different geographical regions ( P <0.001) and countries ( P <0.001).
Excerpts
A repeated‐measures ANOVA revealed a highly significant main effect of state, F(1.80, 1597.20) = 5179.65, p < 0.001 (Greenhouse–Geisser corrected).
Statistical significance was classified as * P < 0.05 (significant), ** P < 0.01 (highly significant), and *** P < 0.001 (extremely significant).
However, a highly significant difference (P<0.001) existed with respect to the control ( Table 1 ).
The best effective group was a combination of curcumin 50 mg/kg with piperine 20 mg/kg which showed extremely significant ( P < 0.001) decrease and increase in ECG and serum biomarker level, respectively, and moderate significant ( P < 0.01) decrease in lipid profile, antioxidant levels, and histopathological score, compared to curcumin alone-treated group.
Results: Administration of Basti and Arjuna Punarnavadi Ghanavati were effective in reducing both systolic and diastolic blood pressure level which was highly significant ( P < 0.001).
Remarkably, the correlations of the GCGN–alanine index became highly significant upon the high protein intake for 6 weeks for IHL (ρ = 0.652, p < 0.001) ( Figure 2B ) and for insulin sensitivity (ρ = 0.644, p < 0.001) ( Figure 2A ).
The concordance between two DE measurements was highly significant ( r = 0.972, P < 0.001; Figure 4A ).
Mediation analysis in patients also yielded a highly significant total effect of PA alpine on QOL ( c = 0.319, p < 0.001; Fig. 3 b).
Specifically, compared to traditional spatial filtering methods CSP and FBCSP, the differences are highly significant ( p < 0.001), with effect sizes of 3.67 and 2.29 respectively, showing that MCFANet has clear advantages in feature extraction.
The results were considered significant at P < 0.05 (*), very significant at P < 0.01 (**), and extremely significant at P < 0.001 (***).
Survey method remained highly significant ( F = 5.74, R 2 = 0.087, p = 0.001), and the proportion of variance explained increased slightly.
The difference (11%) between tests 1 and 3 was highly significant (P < 0.001).
Item 7 “has an intense approach to life” and item 13 “spends his/her day doing things of interest to him/her” were removed due to high fit statistics of 3.03 and 4.36 respectively (>±2.5), and highly significant Chi squared values (p < 0.001).
P < 0.05 was considered as significant, P < 0.01 as moderately significant, and P < 0.001 as highly significant. 5.
A highly significant difference ( P <.001) was found in marginal gap measurements of galvano copings and a significant difference ( P <.05) was found in marginal gap measurements of the laser-sintered Co-Cr copings.
The inter-subject test revealed highly significant differences for focal search (F(1,18) = 14.82, p<0.001) and direct swimming (F(1,18) = 23.31, p<0.001) as well as significant differences for scanning (F(1,18) = 5.78, p<0.05) and perseverance (F(1,18) = 9.87, p<0.05).
All the interactions were highly significant with a P -value < 0.001 (Additional file 3 : Table S3).
This difference was highly significant (t = 8.74, p < 0.001) and associated with a large effect size (Cohen's d = 2.26), supporting the robustness of the functional benefit observed.
Cochran’s Q statistic was highly significant (Q = 703.65, p < 0.001), and the I2 value of 98.72% is very high, indicating that nearly all the variance in study results is not due to chance.
However, when measures of disease comorbidity are added to the equation in Column 3, hospice loses significance ( P = .731) while greater comorbidities becomes a highly significant predictor of hospital admission ( P < .001), as would be expected.
R345W‐ARPE‐EVs induced a highly significant ( p < 0.001) increase in cell migration rate.
In both cases the full model was highly significant (unconditioned— F = 5.20, p = 0.001, adjusted r 2 = 0.467; conditioned— F = 5.43, p = 0.001, adjusted r 2 = 0.409).
Results IL-33 expression showed a positive trend among controls (1/26 = 3.8%), aMCI (9/35 = 25.7%), and AD (17/39 = 43.6%) (trend analysis: P < 0.001).
A notable trend was observed, with older individuals showing a significantly higher incidence rate of hyperlipidemia and diabetes compared to young subjects (p<0.001).