Calculator Inputs
Choose a method, enter grouped counts or values, and submit to calculate a relative effect size with chart-ready output.
Example Data Table
| Scenario | Group A | Group B | Suggested Method | Interpretation Goal |
|---|---|---|---|---|
| Binary outcome study | 42 events from 120 observations | 28 events from 130 observations | Relative Risk or Odds Ratio | Compare event likelihood between two groups |
| Absolute difference review | 35.00% event rate | 21.54% event rate | Risk Difference | Measure extra percentage-point change |
| Performance lift | 84 score units | 72 baseline units | Relative Change | Measure growth from baseline |
| Continuous response study | Mean 84, SD 15, n 40 | Mean 72, SD 14, n 38 | Response Ratio | Compare average response magnitude |
Formula Used
1) Relative Risk
RR = (a / n₁) / (c / n₀)
Here, a and c are event counts, while n₁ and n₀ are total observations. RR above 1 suggests higher risk in Group A.
2) Odds Ratio
OR = (a × d) / (b × c)
b and d are non-event counts. OR above 1 indicates higher odds in Group A. A zero-cell correction can stabilize the estimate when any cell is zero.
3) Risk Difference
RD = (a / n₁) − (c / n₀)
This measures the absolute gap between event rates. It is reported in proportion or percentage-point terms, not as a multiplicative ratio.
4) Relative Change
Relative Change = (New − Baseline) / Baseline
Positive values indicate increase. Negative values indicate decrease. This is useful when comparing a current value against a reference value.
5) Response Ratio
Response Ratio = Mean₁ / Mean₀
The calculator also shows the log response ratio, ln(Mean₁ / Mean₀). If SD and sample size are provided, it estimates the confidence interval on the log scale and converts it back.
How to Use This Calculator
- Select the relative effect method that matches your data type.
- Enter labels for both groups to make the report easier to read.
- For event-based studies, provide event counts and totals.
- For value-based studies, enter means or baseline values.
- Add SD and sample size if you want a confidence interval for response ratio.
- Choose alpha level and decimal precision.
- Submit the form to display the result above the calculator.
- Review the chart, summary table, and export options for reporting.
FAQs
What does relative effect size measure?
It measures how strongly one group differs from another using ratios, percentage changes, or absolute rate differences. It helps summarize practical impact, not just statistical significance.
When should I use relative risk instead of odds ratio?
Use relative risk when you have direct event rates and want intuitive interpretation. Use odds ratio more often in case-control studies or logistic regression summaries.
Why is zero-cell correction included?
A zero in any contingency-table cell can make ratio estimates unstable or undefined. The correction adds a small constant to help calculation proceed more reliably.
What does a confidence interval crossing 1 mean?
For ratio measures like relative risk, odds ratio, or response ratio, an interval crossing 1 means the estimate may be compatible with little or no multiplicative difference.
What does a confidence interval crossing 0 mean for risk difference?
Risk difference is centered around zero. If the interval crosses zero, the data may be compatible with no meaningful absolute difference between groups.
Can relative change be negative?
Yes. A negative relative change means the new value is lower than the baseline. For example, a value moving from 100 to 80 gives a relative change of -20%.
Why use response ratio for continuous outcomes?
Response ratio is useful when proportional comparison matters more than raw difference. It works well for positive means, especially in biological, environmental, and experimental datasets.
How should I report the result?
Report the chosen metric, both group values, and the confidence interval. Add plain-language interpretation so readers can understand direction, size, and practical meaning.