Excerpts

The logistic regression model was statistically highly significant (χ 2 (4) = 28.619, p = 0.000 with df = 4).

The result was highly significant (P = 0.00) suggesting well fitness of the model.

1B ) were highly significant, but their coefficients of determination were lower than those observed for the corresponding soil-to-hepatopancreas regressions (E1 phase: p = 0.000, R 2 = 0.737; E2 phase: p = 0.000, R 2 = 0.581).

Specifically, the calculation results of the meta-analysis revealed a moderately significant relationship between motivation and loyalty (r = 0.420, 95%CI = [0.321–0.505], p<0.000) with 16 observations.

The model was found to be highly significant (R = 0.714; Rsq.. = 0.510; F = 10.661; p = 0.000).

The correlation between samples by PICRUSt metabolic inference was weaker than with our method, but was still highly significant (R 2 = 0.40, p ≈ 0) ( Fig 4D ).

The path coefficient for this relationship is 0.316, and it is highly significant (p-value = 0.000).

Highly significant ( P <0.000 2) genetic variance was expectedly observed among the populations and explained 63.27% of the total variance, supporting the results from the hierarchical and Bayesian clustering.

We found a highly significant (p<0.000) summary SMD of 2.6 with a CI of [2.5, 2.7].

Highly significant differences (p = 0.00) between the index of substitution saturation (Iss) and the critical Iss (Iss.c) were observed for all alignments and site types other than ITS when examining all sites and treating gaps as unknown nucleotides (in which case p = 0.54).

Our logistic regression model was significantly better as it explained more of the variance in the outcome, which was reflected by the highly significant chi-square value (chi-square = 2365.3, df = 17, p < .000).

control comparison was highly significant (p = 0), which indicates a common transcriptomic response in these two MDS subtypes.

In spite of the sample-size differences, an ANOVA comparing the average bursts-in-context LDT 0.75 of experiment 2 to the average burst-in-isolation LDT 0.75 of experiment 1 did reveal highly significant context-interference effects for both /pᴂk/, F(1, 22) = 21.50, MSE = 20.44, p = .00, and /pᴂt/, F(1, 12) = 9.80, MSE = 25.90, p = .01, because in experiment 2 the LDTs were 1.0–5.0 dB larger than those of experiment 1 (see Fig 1 ).

It almost achieved significance for NG (22.9% vs 17.2%; P = 0 , 06 ).

When scores on the first principal component were included in alternative Model 2b together with the variables from Model 2, the component was a highly significant predictor of symptom improvement for both PTSD (HTQ) (β = 0.30 p = 0.000) and depression (HAM-D) (β = 0.25 p = 0.001).

We have also shown that CD4 + CD25 + FOXP3 + T cell frequency in PBMCs when plotted on a ROC curve for ITB and CD patients had a highly significant area under the curve [AUC = 0.908, p = 0.00, 95% CI = 0.82–0.99].

According to the paired t-tests, all of the differences between the estimates yielded by the two methods are highly significant (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 Friedman test was highly significant (p<0.000; Chi square 90.5, df: 8).

The results showed that, though the different weed control methods did not significantly (p>0.05) influence soil infiltration rate, when combined with tillage systems in a factorial design, there was a highly significant interaction effect, p < 0.000, F (6) = 5.530 ( Table 6 ).

However, when the data were re-coded so that the outcome variable was not disease severity, but the occurrence of any stage of the disease, the association was highly significant (χ 2 = 89.000, p = 0.000).

The KS test revealed a highly significant correlation ( p = 0) between CTNNB1 binding and gene expression changes after CTNNB1 knockdown, and this was true with both siRNAs ( Figure 3A and data not shown).

This effect was further shown to be highly significant for each individual marker by reaching Bonferroni corrected significance ( Fig 3 ; univariate F-tests, p < 0.000).

In fact, the analyses demonstrated that partitioning into the major haplogroups explains 67.59% of the overall mtDNA variability and corresponds to a highly significant fixation index ( p <0.000).

According to this t -test, the difference between the PC1 scores for the cached points and the kill/camp points is highly significant ( t = −10.82, df = 120, p <0.000).