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For overlapping and republished studies, only the study with the largest samples was included.
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The largest sample was then chosen, representing 119 groups, classified by department.
The survey with the largest sample was selected for this analysis.
The largest sample was recruited in Germany (n=1444).
Large samples are also important.
Asymptotically optimal designs for large samples are studied.
The OC-SVM is effective when large samples are available for providing an accurate classification.
These data are preliminary and further investigations with larger samples are needed to support our findings.
However, larger samples are needed to confirm this.
However, additional analyses with larger samples are necessary.
Clearly, more research with larger samples is needed to establish which findings are replicable.
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