“marginal significance”

Post-hoc two samples t -tests (one-tailed) for each stimulus class revealed that musicians relative to non-musicians exhibited significantly narrower temporal integration windows for sinewave speech [ t (39) = 2.34, p = 0.025; one-tailed p = 0.01] and piano music [ t (39) = 4.74, p < 0.001], and a marginal significance for natural speech [ t (39) = 1.49, p = 0.14; one-tailed p = 0.07].

None of the individual predictors reached statistical significance ( p s > 0.13), although barriers to screening approached marginal significance ( B = 0.04, SE = 0.03, p = 0.14).

2A? Response: In Figure 2A (IL-1β), the response to pm-PM2.5 was 3.3-fold above control, with marginal significance (p = 0.14).

The same pattern is seen when three participants who detected the manipulation were excluded, with the exception that the intercept for the liking ratings in Experiment 1b now failed to reach marginal significance ( t = 1.519, p = .142).

Besides, concomitant ATM MUT and gene fusions were correlated with lymph node metastasis, with marginal significance ( p = 0.143) (Fig. 2 B).

Predictors not reaching significance (or marginal significance) included material status (OR = 0.70, P = 0.148), household deprivation (OR = 0.94, P = 0.266), urban/rural location (OR = 0.57, P = 0.092), self-rated health (OR = 1.27, P = 0.087).

Among the thirteen lncRNAs, ENST00000671612.1 correlated with worse refractory free survival (RFS); p value = 0.01; and HR = 2.0 (1.1–3.7), as presented in Figure 10 a,b, while ENST00000520619.1 exhibited marginal significance in predicting RFS ( p = 0.15, supplementary Figure S1 ).

Covariates with marginal significance ( P < 0.15) were included in the multivariate logistic regression analysis using a stepwise model selection method.

Variables that achieved statistical significance ( P < 0.05) or marginal significance ( P < 0.15) on univariate analysis were entered into a multivariate Cox proportion hazard model to identify significant independent factors.

Statistical significance was determined at p-value of <0.05 and marginal significance at p-value of <0.15.

Statistical significance was set to p ≤0.05, and marginal significance was set to 0.05< p ≤0.15.

However, marginal significance was observed in the comparison between ICDAS II scores and those generated by laser-induced fluorescence devices ( p = 0.15), as depicted in Figure 5 .

With these two factors taken into account, water which showed only marginal significance in the exploratory analyses was no longer significant ( χ 2 1 = 2.046, P = 0.153).

Again, occupation (farmer/other) showed a negative association with infection probability though with marginal significance (OR = 0.61, 95 % CI: 0.35–1.06) with a p-value = 0.17.

Either CAP exposure or IBRV infection triggered IRF3 and IRF7 overexpression; yet CAP significantly reduced the increased level of IRF7 on IBRV infection back to normal (p = 0.021 for IRF7 at 2-min CAP, p = 0.018 for IRF7 at 4-min CAP, Figure 6a ), and suppressed IRF3 expression with marginal significance (p = 0.171 for IRF3 at 2-min CAP, p = 0.077 for IRF3 at 4-min CAP, Figure 6b ).

Despite the significant reduction in the analgesic score post-treatment ( P = 0.0031), the QLQ-H&N35 revealed only marginal significance concerning the intake of pain killers ( P = 0.1723).

Consequently, 2-miR + ly model was superior to serum SCC antigen with great significance (P = 0.01) and to ly, and clinical T stage with marginal significance (P = 0.18, 0.07, respectively).

Females demonstrated weaker associations—ALT (β = −0.97, p = 0.031) and γ-GTP (β = −1.60, p = 0.015) reached marginal significance, while AST did not (β = −0.51, p = 0.181).

2 ), with marginal significance ( p = 0.189 and 0.059, respectively).

The threshold for statistical significance was p < 0.05, and marginal significance was assumed at 0.05 ≤ p < 0.20.

Predictors of LLIN ownership from the bivariate logistic regression analysis with at least marginal significance of p ≤ 0.2 were fitted to multiple logistic regression model.

The variables with marginal significance (0.05 ≤ p < 0.20), such as sex, infections, and small hospital types, were also included in the multivariable logistic regression model.

For LTBI risk factor assessment, we employed a multivariate logistic regression approach. Variables demonstrating marginal significance ( P < 0.2) in univariate analyses were subsequently included in multivariable modeling.

Birth history and demographic factors such as sex, disability and income were included to model and dietary habits were selected based on backward selection with at least marginal significance (p<0.2) on univariate analysis.

Among variables predicting no reflow, clinically relevant variables with marginal significance (defined as p<0.2) in the univariate analysis were entered into multivariate models to determine predictors of transient and persistent no reflow.