Excerpts

Proportion correct to true items was slightly lower in the Coordinate condition than in the Anomalous condition, F (1,23) = 3.14, 0.05 < p < 0.10, with a slight trend toward the increase being larger for atypical than for typical exemplars, F (1,23) = 2.84, 0.1 < p < 0.2.

The effect of self-efficacy was in the predicted direction but fell short of significance, r = −0.10, p = 0.20.

Albeit there was no significant main effect of the bin number, the magnitude showed a decreasing trend through the test trials [ANOVA: F (59, 2) = 1.75, p > 0.2].

As evident in the demographic data and questionnaire results presented in Table 1 , no significant difference was apparent in terms of gender (χ 2 [1]=1.60, p =0.206), age ( t [31]=0.59, p =0.559), and educational level ( t [31]=−0.90, p =0.377) between the waitlist control and MBSR groups.

Interestingly, albeit marginally significant, students in the control group showed a relative increment in the self-reported use of supplements over time (Use (time1) = 4.9%; Use (time2) = 8.7%; p = 0.22, McNemar Test).

After comparing the last two models, no statistical difference was apparent (Δχ 2 = 1.395, Δ df = 1 , p = 0.237), so we accepted the model A4 as the final model since it showed a better parsimony fit index (AIC = 111.666).

The results associated to the three interaction terms were not significant although a slight trend was observed in the interaction between positive affect and depression [ HR = 1.32; 95% CI = (0.82, 2.10), p = 0.25].

Results from these statistical tests revealed that SBT participants showed an increasing trend in their reporting of malicious messages ( b = 0.21, p = 0.263, Odds Ratio ( OR ) = 1.23, 95% CI [0.56, 1.76]) and a decreasing trend in their reporting of benign, professional networking messages ( b = −0.09, p = 0.516, OR = 0.92, 95% CI [0.70, 1.20]) during skills-based training.

The model of complete independence already fitted the data, G 2 (4) = 2.29, p = 0.68, and no lower-order main effects or interactions approached significance, largest G 2 = 1.15, p = 0.28.

We detected a marginally significant trend of an increased number of saccades on incidence of malaise [0.05 (Nagelkerkes), 0.032 (Cox and Snell), χ 2 = 9.75, p = 0.283].

However, the direction of effects was informative: in the older group, psychological investment showed a positive trend ( β = 0.09, p = 0.29 at T2 → T3) while behavioral time was near zero ( β = −0.01, p = 0.88), consistent with the hypothesis that cognitive processing is more consequential than behavioral exposure.

A tendency for a spatial bias to left-side targets was found after solving subtraction problems, but the difference of RTs to left and right side targets was marginally significant, F (1,26) = 1.078, p = 0.309, η 2 = 0.040.

At the slowest tempo (IOI = 750 ms) and at the fastest tempo (IOI = 450 ms), children and adolescents who stutter tapped more in advance of the pacing event than controls did [750 ms, F (1,59) = 5.67, p = 0.02; 450 ms, F (1,59) = 3.82, p = 0.06, marginally significant; 600 n.s., p = 0.31].

The results showed a trend toward lower FA in the PSA group (MD = −0.04; 95% CI = −0.10 to −0.03; p = 0.32; I 2 = 98%; 72 participants), but the difference was not statistically significant (see Figure 2B ).

The results from these 2x2 ANOVAs did not qualitatively differ from the analysis reported in Section “Results” and the interaction between the factors Evaluation change and explicit self-esteem remained virtually significant in both analyses Analysis 1: no main effect for the factor Evaluation change [ F (1,55) = 0.74, p = 0.39] or the factor explicit self-esteem [ F (1,55) = 2.9, p = 0.09], interaction between these two factors [ F (1,55) = 3.55, p = 0.06]; Analysis 2: no main effect for the factor Evaluation change [ F (1,55) = 0.36, p = 0.55] or the factor explicit self-esteem [ F (1,55) = 0, p = 0.97], interaction between these two factors [ F (1,55) = 3, p = 0.08].

Using paired t -tests, we found that for synesthetes, total fraction dominance was significantly larger for achromatic digits than for achromatic non-digits [ t (11) = 2.3, p = 0.04], whereas no such difference was apparent for controls [ t (11) = 0.8, p = 0.4].

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 ).

Neither of the fixed factors nor their interaction were significant, with only Weather approaching significance: Contrast F (1, 197) = 0.61, p = 0.437; Weather F (1, 6,467) = 3.82, p = 0.051; Interaction F(1, 6,467) = 0.59, p = 0.441.

Results showed that the interaction between Focal Goal Magnitude × Alternative Goal Magnitude (β = −0.14, p = 0.081) as well as the interaction between Alternative Goal Magnitude × Painfulness (β = 0.15, p = 0.057) almost reached significance, whereas the interaction between Focal Goal Magnitude × Painfulness did not (β = 0.06, p = 0.448).

An ANOVA revealed that the influence of the domain size on E ( k ) is highly significant ( p = 5.35·10 −8 ) for normalized slider values but not for unnormalized slider values ( p = 0.457).

Likewise, Model 3 did not improve fit despite an effect of SNS that was almost significant, χ 2 (2, N = 190) = 1.38, Nagelkerke R 2 = 0.15, p = 0.50.

The percentage did not show a significant trend for CPs coming from psychoanalysis (0.03 per year, P = 0.506).

When predicting timed mathematical achievement , the initial marginally significant association with attachment anxiety was reduced to non-significance after taking into account the effect of Math Anxiety (β = -0.07, p = 0.54).

Differences in relaxed positive affect approached significance ( p = 0.55).

Looking at these same correlations controlling for age, we observed a pattern of results very similar to the one with standard scores reported in detail below with only the partial correlation between raw phonological awareness score and visual ISL being near-significant ( r = 0.36, p = 0.56; with p ’s for all other correlations > 0.36). 9 With a low test reliability we can not expect correlations with other outcome measures.