“near-significant”

In order to streamline the model and focus on the most meaningful relationships, only significant and near-significant (i.e., 0.05 < p < 0.10) effects from Model 1 in Model 2 were retained (see Figure 2 ).

Significant (p < 0.05) or near-significant (p ≤ 0.1) interactions were followed by pairwise comparisons.

A near-significant difference was observed on the CBCL rule-breaking subscale, with boys showing slightly higher scores than girls (4.26 vs. 3.10, respectively ~ p < 0.10).

Although the NCT evaluated all possible edges between nodes, only those showing meaningful or near-significant variation (p < 0.10) were presented in Table 3 to ensure interpretability and transparency in gender-based comparisons.

Results of these analyses were largely consistent with our original models, confirming that legacy effects were rarely neutral: 9 of 10 ecosystems had significant or near-significant ( P < 0.1) z -score responses ( Fig. 4 and table S4).

In cases where the overall model showed a significant or near-significant effect (typically p < 0.10), post-hoc analyses were performed to interpret individual group differences.

A stepwise multiple linear regression procedure was performed to evaluate whether any significant ( P < .05) or near-significant ( P < .10) factors from univariate analyses served as independent predictors of increased visual analog scale (VAS) pain scores following second-side surgery.

Statistical analysis Univariate analyses were performed to assess the influence of stratifying factors on clinical CTV coverage by AID-based plans and geometric performance, and subsequent multivariate regressions including significant or near-significant factors (p <= 0.1) from univariate analyses were then performed.

Notable near-significant differences (p < 0.1) are also indicated in the figures.

Deep GM SANDI metrics that showed near-significant differences, defined as unadjusted P < 0.10, were compared for each deep GM region (averaged between the two hemisphere) between people with MS and HC.

were increased by ginseng polysaccharides or oligofructose treatments with significant ( p < 0.05) or near-significant (0.05 < p < 0.1) differences compared with the model group ( Fig. 2c ).

Moderated regression models tested HEI-2020*APOE-ε4 interactions; significant ( p < .05) and near-significant ( p < .10) interactions were followed by simple slope analyses.

Candidate predictors included baseline biomechanical parameters that showed significant or near-significant associations in univariable analyses ( p < 0.10) and/or were considered clinically relevant.

Significant and near-significant (p<0.10) differences were then assessed further for independence in sequentially adjusted linear regression models: adjusting first for demographic factors (age, sex, ethnicity); next for retinopathy, neuropathy and BMI; next for blood pressure and antihypertensive medication; and finally for HbA1c.

The Friedman test examined repeated-measures (within-resident) phase effects, and post-hoc tests were conducted when there was a statistically significant ( p < 0.05) or near-significant ( p < 0.10) effect.

Ecosystem services trade-offs and synergies The NMDS plot and the ANOSIM did not show any significant difference between tillage and drought treatments in terms of global ecosystem services provision, although tillage had a near-significant effect (0.05 < P < 0.10) (Supplementary Fig.

Interaction models that slightly improved model fit (i.e., lower AIC) and included statistically significant (p < 0.05) or near-significant (p < 0.10) interaction terms were reported in place of the main effects model.

The near-significant ( p = 0.1) contribution of parity to the monthly models of the effect of hour for BL18R, BL15R and ST18R, plus the near-significant contribution of age to the June model of BL15R and the near-significant effect of hour on BL18R and ST18R probably excludes these for diagnostic use.

Candidate predictors included baseline biomechanical parameters that showed significant or near-significant associations in univariable analyses ( p < 0.10) and/or were considered clinically relevant.

The multivariate analysis using both significant and near-significant variables (up to P = 0.1 in the univariate analysis) showed that pERK + /pAkt − CTCs remained an independent factor associated with a good prognosis (hazard ratio = 9.389, P < 0.01).

Significant differences were declared at p ≤ 0.05 whereas near-significant trends were considered at 0.05 < p ≤ 0.10.

Only variables that showed significant or near-significant correlations ( p < 0.10) with the dependent variables of interest were selected for further multiple linear regression analyses.

A paired t test showed significant differences at p < 0.05 for HCB and CN and near-significant differences at p < 0.1 for TC and CC, but not for TN, HEPX nor ENDO-I.

P values indicated on figures are for the significant (P<0.05) or near-significant (0.05<P<0.1) factor that has been plotted.

Post hoc pairwise comparisons of the number of SRCs at different time intervals—thereby representing policy and rule changes—were performed using Tukey tests for significant or near-significant ( P < .10) models.