Barely Significant
← all phrases

“marginally nonsignificant”

449 sentences · 449 papers · 520 search hits before verification · confirmed specimen

Sighted at

p=0.096

Listed by Hankins (2013) · Otte et al. (2022)

In the literature

Careful examination of PCO (Figure 3 b; 60.1% variation explained), MDS (not shown), and PERMDISP ( F 2,69 = 2.91, p = .072, deviation from centroid; “0%”: 31.0 ± 1.7, “50%”: 28.1 ± 1.4, “100%”: 26.2 ± 1.1) suggests that these differences may partly be explained by the homogenization of community structure with increased turf density (i.e., marginally nonsignificant reduction of multivariate dispersion). 3.4 Prevalence of habitat formation in shaping associated assemblages The total SF volume did not influence MF, but ecospace (i.e., interstitial volume created among SF) had a significant effect on richness, abundances, and community structure of MF (Table 2 ).
A similar impact is observed for nonfatal MI alone, while the risk reduction for CHD death is slightly reduced, going from being marginally significant using the original or hospitalised WOSCOPS events to marginally nonsignificant using the RL events.
We found that males appeared to be more likely to stay if a related male was present at group entry compared to males who did not have a male relative upon entry into a group (GLMM, N = 18 without related males, 66% stayed for a year, N = 17 with related males, 94% stayed for a year, χ 2 ML : P = 0.060, Table 2 ), although this was marginally nonsignificant.
1 In 2010, Bolland et al 2 reported a meta‐analysis of 8 randomized clinical trials in which calcium supplements in monotherapy (CaM) were associated with a significant increased risk of acute myocardial infarction (AMI; relative risk: 1.27; 95% confidence interval [CI], 1.01–1.59) and a marginally nonsignificant increased risk of stroke (relative risk: 1.12; 95% CI, 0.92–1.36).
No topics representing advanced quantitative concepts except Machine Learning significantly contribute to the difference between associate's and baccalaureate institutions and master's and doctoral institutions, although two topics (Data Manipulation and Mechanistic Models) are marginally nonsignificant. 4 DISCUSSION AND RECOMMENDATIONS FOR NEXT STEPS 4.1 Gaps are visible in the existing resources at each curriculum level Previous literature has discussed the importance of understanding the current curriculum landscape as a first step in improving curriculum in higher education (NASEM, 2020 , 2021a ; Rawlings‐Goss et al., 2018 ).