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Since publication bias was suggested by the funnel plots, we excluded the three studies with the highest standard errors for the analysis of pooled effect across studies in the high exposure category.
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No sample bias effect was observed (p>0.05), except for the Palaemonidae (p<0.05), which also exhibited the highest standard error variation (SE) value.
After exclusion of the three studies that had the highest standard error, because of suspected publication bias, the pooled effect sizes for studies in the high-exposure category was 2.94 (95% CI 1.89 4.59).
In addition, phenotypic prediction accuracies were only slightly increased by including dominance effects for growth traits since estimates of non-additive variances yielded rather high standard errors.
Contour enhanced funnel plots showed that for anxiety (Fig. 5), most of the studies with higher standard errors had results overcoming conventional statistical threshold of p < 0.05, with a considerable proportion of these even significant at the more conservative threshold of p < 0.01.
The computed uncertainties in the system salinities seem to be larger with higher standard errors (S.E).
However, the coefficient is never statistically different from zero due to the higher standard errors.
Due to high standard errors, these changes were not statistically significant.
In settings for which the estimations reached a maximum, we encountered the problem of very high standard errors.
The standard 2T4k model resulted in outcome measures and rate constants that could not be determined reliably (i.e. very high standard errors [SEs] of fitted parameters).
Nevertheless, the identification of such complex moderations is often subject to high standard errors and broad confidence intervals (Afshartous and Preston 2011).
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CEO of Professional Science Editing for Scientists @ prosciediting.com