“marginally significant”

To evaluate independent factors associated with ICU mortality in this identified subgroup of patients, significant or marginally significant ( p < 0.10) bivariate risk factors were examined using univariate and multivariable backward stepwise mixed logistic regression stratified on the center.

Among the metabolites that showed a trend toward statistical significance ( p < 0.1) in the pattern search results within the Probiotic group, five compounds—threonic acid, L-proline, N-oleyl-leucine, threonine-conjugated chenodeoxycholic acid, and N-methylglutamic acid—exhibited marginally significant differences ( p < 0.1, t -test) between 0-week baseline and the 4-week endpoint in the Probiotic group ( Fig. 7B ).

The study used a within-subjects comparison of cortisol decline (pre and post); a larger sample size might enable between-subjects comparison of cortisol regulation and testosterone levels (high and low levels), and a larger sample size might benefit the marginally significant effects (trend-level significance, p < 0.10).

Multivariate logistic regression analysis was performed to assess the risks of mortality and poor outcomes during hospitalization, adjusting for clinical variables identified by univariate analysis as showing significant or marginally significant (0.05 ≤ P < 0.10) differences between the presence or absence of each outcome.

The effect of product type × reward type was significant [ F (1, 288) = 12.99, p < 0.001]; that of product type × gender was insignificant [ F (1, 288) = 0.26, ns]; and that of reward type × gender was marginally significant [ F (1, 288) = 3.85, p < 0.1].

In contrast, the relationships between CSC indices and SEs were weak ( P > 0.05); and if marginally significant ( P < 0.1) they were negative ( Fig. 5 and SI Appendix , Tables S7 and S8 ).

Results among the females in our sample only partially supported this hypothesis—there was a marginally significant association between mortality and the probability of being liberally religious in 1971, 1988, or 1997 ( β = 1.52, p < 0.10), but no association with the probability of being weakly or privately religious.

Differences are indicated as significant ( p < 0.05; different letters) and marginally significant ( p < 0.1; asterisks), following least significant difference post hoc tests.

In TMT‐B, the Type C group (201.69 ± 87.24) showed a significant decrease compared to the Type A group (194.80 ± 98.82) ( p < 0.05) and marginally significant decrease compared to the Type B group (283.14 ± 109.07) ( p < 0.10).

As shown in Table 3 , the interaction term of cases and openness was significant ( b = −0.418, SE = 0.153, p = 0.007), and the interaction term of cases and conscientiousness was marginally significant ( b = −0.163, SE = 0.099, p = 0.10).

All data are reported as least square means and considered statistically significant at P ≤ 0.05 and marginally significant at 0.05 < P ≤ 0.10.

Risk factors were first explored using a univariate analysis; those which showed at least a marginally significant association ( P < 0.1) were then considered as candidates for a subsequent forward stepwise multivariate logistic regression.

4 The results of Model 9 in Table 3 showed that the effect of organizational-level HPWS on employee experienced HPWS was marginally significant (Model 9, γ = 0.104, p < 0.1).

Results Significant ( P < 0.05) or marginally significant ( P < 0.10) effects of 0.50–0.65 kg were found at all time points (except 9 mo) in arm A.

All statistically marginally significant prognostic factors which identified by univariate analysis ( P < 0.1) were entered into a Cox proportion hazards regression model with forward stepwise (Likelihood ratio) to identify independent predictors of VAP event.

Among the 10 genes in PTENPATHWAY, the association of PTK2 copy numbers with cigarette smoking was highly significant; the association of MAPK1 , SOS1 , and PIK3R1 were marginally significant ( P < 0.1).

Between the glocal identity type corner and local identity type corner (Point D) this difference was marginally significant ( p < .10).

In the case of blocked nose, throat irritation and bodily pain, the differences were marginally significant ( p -value< 0.1).

All results were considered significant at P < 0.05 and marginally significant at 0.05 ≤ P < 0.10.

The difference between these responses was marginally significant ( P = 0.10).

Measures that were at least marginally significant (p=0.10) were retained in the multivariate analyses.

There was a marginally significant effect between weeks of telecommuting on two domains—distraction, F (3, 2015) = 2.11, p = 0.10, and work-life effectiveness, F (3, 2015) = 2.11, p = 0.10.

All variables significantly associated with general cognitive scores in the bivariate models (p<0.2) were included in the multivariate model, and only retained if they had an at least marginally significant association (p<0.1) or modified the coefficient by at least 5% [32] , [33] , [38] .

As the objective of this analysis was to investigate the effects of land‐use changes on network indices, we constructed piecewise SEM s only when we found the significant or marginally significant effect of land‐use changes on the indices ( p < .1, see Table 2 ), which results in five separate piecewise SEM s (the effects of abandonment on pollination network connectance, diversity, and generality; the effects of intensification on pollination network connectance, and herbivory network generality).

In addition, in Model 3 the influence of an “integration” ethnic orientation went from non-significant to marginally significant (p < .10) and the influence of an “attenuation” ethnic orientation went from significant at p < .05 to non-significant.