When analyzing meta-analysis results, a narrow confidence interval indicates what?

When analyzing meta-analysis results, a narrow confidence interval indicates what?

• A. Less certainty about the estimate
• B. Greater precision of the estimate
• C. Increased sample bias
• D. Higher effect size

Answer: (B)

A narrow confidence interval indicates greater precision of the estimate in the context of meta-analysis results. This precision means that the estimate of the effect or relationship being evaluated is more reliable and that there is a strong consensus among the included studies regarding the effect size. In practical terms, a narrow confidence interval suggests that if the study were to be repeated, the results would likely fall within this range, reinforcing confidence in the findings. The width of the confidence interval reflects the degree of variability or uncertainty around the effect estimate. Therefore, when the interval is narrow, it signifies that there is minimal variability in the results, thus providing a clearer and more focused estimate of the effect size or relationship being examined. A greater precision reduces the likelihood of random error influencing the results, which is highly desirable in evidence-based practice.

A narrow confidence interval indicates greater precision of the estimate in the context of meta-analysis results. This precision means that the estimate of the effect or relationship being evaluated is more reliable and that there is a strong consensus among the included studies regarding the effect size. In practical terms, a narrow confidence interval suggests that if the study were to be repeated, the results would likely fall within this range, reinforcing confidence in the findings.

The width of the confidence interval reflects the degree of variability or uncertainty around the effect estimate. Therefore, when the interval is narrow, it signifies that there is minimal variability in the results, thus providing a clearer and more focused estimate of the effect size or relationship being examined. A greater precision reduces the likelihood of random error influencing the results, which is highly desirable in evidence-based practice.