Low within-group variance and larger sample sizes are key factors contributing to more overlap scores between comparison groups.
Within-group variance plays a critical role in determining the overlap scores between comparison groups. In statistical analysis, low within-group variance leads to more overlap scores between comparison groups. Larger sample sizes also contribute to more overlap scores by providing a better reflection of the population variance, as larger samples help reduce the effect of subtracting 1 in the formula for sample variance. Additionally, larger effect sizes contribute to more distinguishable differences between groups, aiding in clearer comparison outcomes.
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