These results were confirmed by a mixed ANOVA on the Fisher-z-transformed correlation values, for which the interaction of within-participant (rating dimension) and between-participant factor (across-group comparison) became highly significant [ F (22,32967) = 1781.268, p < 0.001, n2 = 0.178].
Excerpts
Moreover, the second-step modeling revealed a clearly significant full-null model comparison (χ 2 = 185.6, df = 69, p < 0.001) indicating that cycle number and/or species (monkey or human) and/or stage (discrimination or reversal) and/or feature (color, direction, or shape) and/or any of the interactions between them or with training type significantly contributed to the response.
The likelihood-ratio comparison between these two nested models is highly significant ( X 2 10 = 759.46, p < 0.001), suggesting that item-level residual dependence should not be ignored.
The ANOVA result remained highly significant ( p < 0.001) when considering the valence dimension as well.
Students in the experimental group reported substantially lower levels of anxiety (M = 2.71) than those in the control group (M = 5.84), with a highly significant difference ( t = −17.91, p < 0.001).
Given these rigorous metrics alongside highly significant factor loadings ( p < 0.001), the convergent validity and internal reliability of the developed scale are conclusively verified.
Indeed, separate age group analyses confirmed that the phrasal planning effect was highly significant for both young (40 ms, 4.6% benefit, p < 0.001) and older (41 ms, 4.0% benefit, p < 0.001) adults.
With respect to the How Confident section, the seven-factor model demonstrated a statistically and practically significant improvement in model fit as compared to the five-factor model, Δχ 2 (11) = 2645.780, p < 0.001, ΔTLI = 0.041; first six-factor model (A), Δχ 2 (6) = 958.617, p < 0.001, ΔTLI = 0.013; and second six-factor model (B), Δχ 2 (6) = 1969.970, p < 0.001, ΔTLI = 0.031.
Table 3 shows that after controlling for these factors, the profile main effect remained highly significant for all nine subtests (all p < 0.001).
As hypothesized, ELE emerged as a highly significant positive predictor of WTC ( β = 0.62, t = 17.48, p < 0.001).
This study also revealed a moderately significant positive relationship between function value and GPA ( β = 0.21, p < 0.001).
Non-normality was suggested by histograms, Q-Q plots, and highly significant Kolmogorov–Smirnov tests [all D (89) > 0.21, all p < 0.001].
The Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy showed the data for Section 1 to be factorable (KMO = 0.856), Bartlett’s test of sphericity was also highly significant (χ 2 = 2868, df = 36, p < 0.001).
The salience maps were compared pairwise in terms of the Area Under Curve (AUC) for each banner (Le Meur and Baccino, 2012 ); the average correlation was highly significant ( r = 0.81 p < 0.001).
This showed a highly significant main effect of emotional expression [F(1, 13) = 21.6, p < 0.001] and a marginal effect of presentation [F(1, 13) = 4.4, p = 0.06], while the interaction between the two factors was not significant [F(1, 13) = 0.14, p > 0.1].
Paired comparisons show that the difference between structures is highly significant in the learner group [ t (62.9) = 4.91, p < 0.001, gender mean = 62.8, SD = 14.1; non-finite verb mean = 79.5, SD = 17.3].
The difference between these two syllable types is highly significant (sign test p < 0.001), as 22 of the 23 speakers have more pulses in the case of the coda condition.
This difference was highly significant, t (308) = 8.24, p < 0.001, d = 1.02 2 .
Even when this distribution is dropped to have 10,000 randomly selected comparisons from each condition, there is still an extremely significant difference of F (1,19,999) = 1,004.58, p < 0.001.
The parsimonious model remained highly significant, F (6, 5230) = 477.30, p < 0.001, explaining 35.4% of variance ( R 2 = 0.354, Adjusted R 2 = 0.353).
Comparing the accuracies of the four participants to the combined accuracies of their permuted data yielded a highly significant difference at the group level ( t = −5.0, p < 0.001).
Differential associations of support system profiles with resilience One-way ANOVA results indicated highly significant differences in total resilience and all dimension scores across the support system profiles ( p < 0.001), with effect sizes (η 2 ) ranging from 0.100 to 0.107, indicating moderate to large effects (see Table 6 ).
The difference between PF-A and RO-A (independent of conditions) proved highly significant with large effect size in a Chi-square test between BRI = 1 and BRI = 0, χ 2 (1, N = 89) = 33.5, p < 0.001, w = 0.61, indicating that PF-A is strongly associated with body reference, while RO-A is not.
For instance, a mobile app that guides users in applying acupoint tapping protocols for anxiety and stress was investigated in a large-scale study including 270,461 app users and found highly significant ( p < 0.001) symptom reduction ( Church et al., 2020 ).
The difference was highly significant (one-tailed paired t -test: t 11 = 6.98, p < 0.001).