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Effect-size converter

Pubrica’s free effect-size converter expresses one effect as Cohen’s d, Hedges’ g, a correlation coefficient and an odds ratio. Enter the value you have and the two group sizes to see each equivalent with its confidence interval, which helps when combining studies in a meta-analysis or interpreting published results.

The tool runs in your browser. No registration, email address or file upload is required, and the formula, reference or assessment criteria used are shown with the result.

Every tool
  • Runs in your browser
  • Nothing uploaded or stored
  • No email asked for
  • Method shown with the answer
  • Sources dated

The Tool

Convert an Effect Size Between d, g, r and Odds Ratio

Converts an effect between Cohen’s d, Hedges’ g, a correlation and an odds ratio, carrying the confidence interval through each conversion.

02

Converts an effect between Cohen’s d, Hedges’ g, a correlation and an odds ratio, carrying the confidence interval through each conversion.

d · g · r · odds ratio

Limitations

What This Tool Does Not Cover

Use the result as a starting point. These are the situations in which it needs specialist review.

The calculators

Limitations of the calculators

The sample size calculator gives the closed-form answer for two independent groups. Cluster randomisation, interim analyses, a non-inferiority margin, repeated measures and competing risks each change the number materially, and none of them can be handled by inflating the answer afterwards. The same applies to the test chooser: it cannot know that your observations are clustered within clinics, and clustering overrides almost everything else it would tell you.

Method

Methods and Sources

The calculation or reference set behind this tool. The result panel also shows the formula or criteria used.

Effect sizes

Hedges, Hasselblad

Hedges’ small-sample correction for g; the Hasselblad–Hedges transform between d and the log odds ratio; the standard error of d from the two group sizes. Interval limits are converted through the same monotone transforms as the estimate.

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