Confidence intervals can be used and are easily calculated based on information supplied in meta-analyses. However, where average effects need careful interpretation, and where appropriate commentary about the moderators that seemed to affect the average, providing confidence intervals can provide a false sense of precision.
Articles in this section
- Why does the Visible Learning research use effect sizes?
- Why do you use an effect size of d=0.40 as a cut-off point and basically ignore effect sizes lower than 0.40?
- What is the preferred timescale over which an effect size can be calculated?
- Is there a bias when using effect sizes in favor of lower achieving students?
- What caution should I take when calculating an effect size?
- Why are effect sizes used when conducting meta-analysis?
- Why can an effect size of 0.40 be gained in a shorter timeframe?
- Can effect sizes be added (or averaged)?
- How accurate are the conclusions drawn from meta-analysis?
- How can the variability associated with each influence be evaluated?