“marginal significance”

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.

The initial multivariable logistic regression model adjusted for core sociodemographic variables (age group, gender, and ethnic group), along with variables that were significant or showed marginal significance ( P <.20) in univariate analysis.

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.

BRCA samples treated with paclitaxel showed marginal significance ( P = 0.20, Fig. 4C ), although the group annotated with complete or partial response had significantly higher response than the group with stable or clinical progressive disease ( P = 0.03, Fig. 4D ).

This threshold was chosen to retain paths with marginal significance (p < 0.20) that may hold theoretical relevance in this exploratory context, following recommendations for SEM in behavioral research ( 160 ).

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.

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.

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

Variables demonstrating marginal significance ( P < 0.2) in univariate analysis were retained for subsequent multivariate analysis, while those consistently non-significant ( P ≥ 0.2) were excluded.

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.

Factors that showed at least marginal significance from the univariable analysis ( p -value <0.2) were included in the multivariable analysis to account interrelationships among the variables.

While smoking history and a family history of diabetes showed marginal significance in the baseline data ( p = 0.21 and 0.09, respectively), they showed substantial significance in the analysis of the first follow-up data ( p = 5.89 × 10 −5 and 3.88 × 10 −3 ).

Using 1 ng of template reduced the proportion of chimeric reads compared to 10 ng but only with marginal significance ( p =0.22) (see Fig. 5 b ).

After adjusting for sex and APOE-ε4, the associations between tau NEO and cognitive measures were further reduced, with only marginal significance remaining for PACC (β = -0.087, p = 0.233) and DLM (β = -0.126, p = 0.108) in some models.

Notably, the previously observed marginal significance for the ISR OCD scores in the full sample was not replicated in the clinical group (b = 1.62, p = .240).

Variables for multivariable models were selected based on univariable associations with at least marginal significance (p ≤ 0.25) and were fitted using backwards-stepwise elimination.

Variables that showed statistical significance or marginal significance ( p < 0.25, according to the Hosmer and Lemeshow criterion) in the univariate analysis were included in a multivariate logistic regression model using the Enter method.

Those variables demonstrating a bivariate association with at least marginal significance of ( P < 0.25) were included in a multivariable model.

Those variables demonstrating a univariate association with at least marginal significance ( P < 0.25) were included in multivariate logistic regression.

TD prevalences were 9.7 percent in the PTSD sample (n = 31) and 28.6 percent in the controls (n = 7), a three- fold difference with marginal significance (X2 = 1.78, p < .25).

TMB value showed a linear correlation with the number of reported SNVs with marginal significance (Pearson’s correlation coefficient, 0.096; p=0.432) ( Fig. 3A ).

While error rate did not differ between the two notations, place-value notation comparisons were slower to solve than sign-value tasks with marginal significance, F (1,8) = 0.679, MSE = 0.015, p = 0.434 for error rate and F (1,8) = 4.182, MSE = 1,062,876, p = 0.075 for RT (Figure 10 ).

When this study was set aside, there was marginal significance with a conservative effect estimate of 1.11 (95% CI: 1.03–1.19, I 2 = 0%, p = 0.56).

Only signal intensities of the posterior cervix showed marginal significance in predicting labour ( p = 0.567).

During Pregnancy taking iron tablet/syrups showed marginal significance (AOR = 1.36; p = 0.71), likely indicating reverse causation, where high-risk pregnancies receive more supplements.