“marginally significant”

Multivariate Cox regression analysis, including the significant predictors above and the marginally significant ones ( P < 0.10) (including age, hypertension, and dyslipidemia) in the univariate model, showed that low eGFR, poor LVEF, and the absence of statin treatment were independent predictors of death in CKD patients after PCI (Table 4 ).

The interaction between SLM training and gender is also positive and marginally significant (β = 0.0.315, p < 0.1 ).

Results were considered significant at P ≤ 0.05 and marginally significant at P ≤ 0.10.

Marginally significant ( 0.05 < p < 0.1 ) and statistically significant ( p < 0.05 ) volume differences are shown in Table 2 as boldfaced and italicized boldfaced values, respectively.

Results were deemed statistically significant at P <.05 and marginally significant at P <.1.

Vaquitas and NP2 harbor porpoises also displayed marginally significant NI values ( NI > 2, p -value ≤ 0.10; Fig. 4 a).

Potential predictors are defined as variables with at least a marginally significant association (p<0.10) with the outcome.

The longitudinal association between extraversion and sick leave days was marginally significant ( p < 0.10).

A marginally significant association ( p < 0.10) was found for non-small cell carcinoma (HR, 1.05; 95% CI, 0.99–1.11).

In contrast, in patients without active bleeding, multivariate analysis revealed that direct clipping was associated with significantly lower rates of early and late rebleeding (both p < 0.05) and marginally significant lower rates of blood transfusion requirement and IVR need during hospitalization (both p < 0.1).

As described previously, we confirmed the influence of seasonality on the results of the question items of “Frequently purchased goods.” The results indicate that consumer electronics, medicine, and cosmetics showed marginally significant increases or statistically significant increases ( p < 0.10 or 0.05, respectively).

Additionally, the use of public transportation was marginally significant ( p < 0.1).

In contrast, the T-test for autonomy indicated only a marginally significant effect (one-tailed p < 0.1).

Across species, g min tended to decrease with increasing LMA but although this trend was consistent, it was only significant for g min at 35°C ( F 1,21 = 6.6, P = 0.0178, R 2 = 0.23) and marginally significant ( P < 0.1) at 32 and 40°C (Fig. 5 ). g min did not scale with leaf dry matter content or stomatal density at any temperature (data not shown).

Moreover, the path from age to reappraisal was marginally significant ( p < .10), and no age effect was observed on suppression.

As can be seen in the figure, children showed significant shape responding for the clay, M = 0.64, t (74) = 5.16, p < 0.0001, and wood sets, M = 0.68, t (73) = 5.90, p < 0.0001, and marginally significant shape responding for the sand, M = 0.56, t (73) = 1.89, p < 0.10, and Styrofoam sets, M = 0.55, t (74) = 1.76, p < 0.10.

In the sensitivity analysis that considered marginally significant correlates (ie, p < 0.1), we additionally included IADL and contact with healthcare systems to logistic models.

Public religiousness had a marginally significant effect on recovering addicts’ after-treatment abstinence (β = 0.199, p < 0.1), with the increased odds of 22%.

Furthermore, as hypothesized in H3a and H3b, we found a marginally significant positive correlation between BS and Machiavellism ( r = .12, p < .10), representing a small effect and a significant correlation between BS and agentic values ( r = .31, p < .01), representing a moderate effect.

Results show that the significant effects remain the same, with one exception, namely, that the second‐level predictor social opportunity goes from being marginally significant ( p < .1) to being significant ( p < .05) when the 595 moments were excluded.

To evaluate independent factors associated with NOSVA (time-dependent variable), significant or marginally significant univariate risk factors ( p < 0.10) recorded prior or at the time of the first episode of NOSVA, were examined using backward stepwise multivariate Cox proportional-hazards regression model; septic myocardial dysfunction and patient severity as assessed by SAPS II score at ICU admission were also included in the model; thus, the five variables included in the model were SAPS II score at ICU admission, age, septic myocardial dysfunction, renal and non-renal SOFA scores at day 1 of septic shock.

We included those comorbidities that were marginally significant (p<0.1) in the univariate analysis to the multivariate model.

In this version we addressed the two points raised during the revision process, namely data duplication (figure 2 was eliminated, table 3 was maintained) and data display on table 3, which now depicts only significant (p < 0.05) and marginally significant (p ≤ 0.10) correlations.

Bivariate analysis focused on identifying covariates that showed at least a marginally significant (p-value ≤ 0.10) association with SEQ-12 score.

After adjusting for comorbidities and ADL limitations in the next model, the coefficient for the age difference became negative and was marginally significant (−.07, P < .10).