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For comparison of means, single factor analyses of variance (ANOVA) were used.
The findings confirm previous single factor analyses and demonstrate that nine of the factors are independently associated with survival.
For statistical analysis, IBM SPSS Statistics Version 22 was used and single factor analyses of variance (ANOVA) were performed to test for differences between data groups.
Single factor analyses of the influences on service fees were performed via correlation analyses followed by multiple linear regression for the multivariate analysis.
Similarly to single factor analyses, a correction of the p-values for multiple testing was performed using the Benjamini-Hochberg method.
Deceptively, correlations between homo-oligomerization and noise or plasticity were weak to non-existent in single factor analyses (Table 1, Table 2, Figure 2), where stickiness is a confounding factor.
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Model 1 includes the statistically significant factors from the single-factor analyses without including interactions.
Subsequently, single-factor analyses were performed separately between the 2 asymptomatic subgroups and the symptomatic tear group.
Single-factor analyses were performed between the main groups, and odds ratios, 95% CI, and p-values are given.
For single-factor analyses, statistical comparisons of colonization between groups were made using either the Kruskal-Wallis test with Dunn's post test or t tests, as appropriate.
Among feeding factors, full breastfeeding at week five more than doubled the likelihood for being introduced to solid food at a later age (OR = 2.52 CI: 1.93-3.28) (Table 2).> -wrap-foot> Note: Model 1 included all main effects of factors that were statistically significant in single-factor analyses.
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