# Blinded sample size re-estimation in equivalence testing

## TL;DR

This paper examines how blinded sample size re-estimation can lead to increased type I error rates in equivalence testing, especially with small sample sizes, and provides theoretical and simulation insights.

## Contribution

It explains why type I error inflation occurs in equivalence testing during blinded sample size re-assessment and quantifies this effect through simulations and theory.

## Key findings

- Type I error violations are more pronounced in equivalence testing than superiority testing.
- Small sample sizes during blinded re-assessment lead to significant error inflation.
- The paper provides theoretical derivations and simulation results quantifying error inflation.

## Abstract

This paper investigates type I error violations that occur when blinded sample size reviews are applied in equivalence testing. We give a derivation which explains why such violations are more pronounced in equivalence testing than in the case of superiority testing. In addition, the amount of type I error inflation is quantified by simulation as well as by some theoretical considerations. Non-negligible type I error violations arise when blinded interim re-assessments of sample sizes are performed particularly if sample sizes are small, but within the range of what is practically relevant.