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Impacts of Random and Fixed Effect Models on Type I and Type II Errors in Bioequivalence Hypotheses in Crossover
Elif Ertas1, Semra Erdogan2, Emine Arzu Kanık3
1Department of Biostatistics, Selcuk University, Konya, Turkey.
Therapeutic Innovation & Regulatory Science
|June 12, 2026
Summary
The US-FDA random effect model offers higher statistical power for bioequivalence studies compared to the EMA fixed effect model, especially in borderline cases. Inter-period correlation significantly boosts power, crucial for efficient trial design.
Area of Science:
- Pharmacokinetics and Pharmacodynamics
- Biostatistics
- Drug Regulatory Affairs
Background:
- Bioequivalence (BE) is essential for generic drug approval.
- Global harmonization efforts like ICH M13A exist.
- Statistical modeling differences persist between EMA (Fixed effect) and US-FDA (Random effect) frameworks regarding the 'subject' term.
Purpose of the Study:
- Evaluate statistical paradigms (Fixed vs. Random effect) on Type I Error (TIE) and Statistical Power.
- Assess impact of sample size, intra-subject variability (CV), and inter-period correlation.
- Compare EMA and US-FDA statistical approaches for bioequivalence.
Main Methods:
- Conducted 1.89 million Monte Carlo simulations for a 2x2 crossover design.
- Varied parameters: sample size (12, 24, 32), CV (15%, 25%, 30%), inter-period correlation (0.30, 0.60, 0.90), GMR (1.00-1.10).
- Analyzed data using EMA (Fixed) and FDA (Random) ANOVA specifications.
Main Results:
- Both models controlled Type I error at the 5% level.
- FDA Random Effect model showed significantly higher statistical power in borderline scenarios (GMR 1.03-1.05).
- Increased inter-period correlation substantially amplified statistical power, comparable to doubling sample size.
Conclusions:
- Model discrepancies are critical for global drug development under ICH M13A.
- The FDA model is slightly more permissive, reducing manufacturer risk without compromising safety.
- Incorporating inter-period correlation in power calculations is recommended for efficient bioequivalence trials.
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