Confidence Interval Formula:
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The Absolute Risk Reduction (ARR) Confidence Interval provides a range of plausible values for the true treatment effect in a clinical study. It quantifies the uncertainty around the point estimate of ARR and helps determine if the observed effect is statistically significant.
The calculator uses the standard confidence interval formula:
Where:
Explanation: The formula calculates the margin of error around the ARR point estimate, providing a range where the true population parameter likely falls with 95% confidence.
Details: Confidence intervals are crucial for interpreting clinical trial results as they provide information about the precision of the estimate and help assess clinical significance beyond statistical significance.
Tips: Enter the Absolute Risk Reduction as a proportion (e.g., 0.15 for 15%) and the Standard Error. Both values must be positive, with ARR typically between 0 and 1.
Q1: What does a 95% confidence interval mean?
A: It means that if the same study were repeated many times, 95% of the calculated confidence intervals would contain the true population parameter.
Q2: How is standard error calculated for ARR?
A: Standard error for ARR is typically calculated using the formula: \( SE = \sqrt{\frac{p_1(1-p_1)}{n_1} + \frac{p_2(1-p_2)}{n_2}} \), where p₁ and p₂ are event rates in treatment and control groups.
Q3: When is ARR considered statistically significant?
A: When the 95% confidence interval does not include zero, indicating the treatment effect is unlikely due to chance alone.
Q4: What's the difference between ARR and RRR?
A: ARR is the absolute difference in event rates, while RRR (Relative Risk Reduction) is the proportional reduction in events compared to control.
Q5: Can I use this for other confidence levels?
A: This calculator uses 1.96 for 95% CI. For 90% CI use 1.645, for 99% CI use 2.576 as the z-score multiplier.