Power Analysisfor poisson Regression Calculator Guide
Power: Poisson Regression
Power depends on expected rate differences (effect size), α, covariates, dispersion, and sample size or exposure time.
Key Inputs
- Effect size (rate ratio or log coefficient)
- α (significance level)
- Sample size / exposure
Example
Detecting a rate ratio of 1.3 at α=0.05 typically requires larger n than for 1.5, given the same variance and exposure.
FAQs
Overdispersion?
Use robust methods or quasi-Poisson; it reduces effective power.
Offsets?
Include log exposure in the model to scale rates.