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Once corrected for publication bias the relationship between the impairment of emotion recognition and major depression remained robust, although this overall effect size was reduced (d = −0.42, 95% confidence interval: −0.62 to −0.23) relative to that estimated from the original data.
Findings for coronary heart disease were similar in meta-analyses restricted to studies that adjusted for conventional vascular risk factors (relative risk 1.42, 95% confidence interval 1.17 to 1.73); studies with ≥200 cases (1.44, 1.20 to 1.74); studies with a high quality score (1.53, 1.22 to 1.92); and in analyses that corrected for publication bias (1.34, 1.12 to 1.60).
Similar(58)
Correcting for publication bias, we estimated the odds ratio to be 1.15 (95% CI 0.98-1.32, not significant).
Simonsohn, U., Nelson, L. D. & Simmons, J. P. p-Curve and effect size: correcting for publication bias using only significant results.
Meta-analyses of quantitative estimates should correct for publication bias and study heterogeneity [17], which is difficult with small samples.
Correcting for publication bias is important to avoid giving too much weight to studies that reflect selection by investigators or others involved with publication processes.
Correcting for publication bias suggested that the depletion effect was statistically no different from zero, although not all scholars agree with these methods of correction.
Overcoming, detecting and correcting for publication bias is problematic.
We have not attempted to try to correct for publication bias for four reasons.
Applying a trim-and-fill analysis (designed to correct for publication bias, if any) made negligible difference to the mean.
We used a trim and fill method to correct for publication bias and minimised heterogeneity by using well-defined clinical subgroups for the assessment of outcomes.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com