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Bioequivalence revisited: non-parametric analysis of two-period cross-over studies
This study explores non-parametric bioequivalence procedures for treatment, period, and sequence effects in crossover studies. A FORTRAN program (BIOEQNEW) is presented for calculating non-parametric confidence intervals and estimates.
Area of Science:
- Biostatistics
- Pharmacometrics
- Clinical Trial Design
Background:
- Existing non-parametric bioequivalence methods focus primarily on treatment effects.
- Computer implementation of these methods, including specific algorithms, requires detailed exploration.
- Extending non-parametric approaches to period and sequence effects offers a more comprehensive analysis.
Purpose of the Study:
- To explore Hauschke et al.'s non-parametric bioequivalence procedure for treatment effects.
- To investigate computer implementation aspects, including Meineke and De Hey's algorithm and a recursive algorithm.
- To extend non-parametric analysis to period and sequence effects, analogous to analysis of variance in two-period crossover studies.
Main Methods:
- Development and presentation of a FORTRAN program (BIOEQNEW) implementing Meineke and De Mey's algorithm.
- Generation of a table of indices for ranked intersubject-intergroup mean ratios or differences for up to sixty subjects.
- Application of non-parametric methods to treatment, period, and sequence effects in two-period crossover studies.
Main Results:
- A table is provided to establish non-parametric 90% confidence intervals for studies with up to sixty subjects.
- The non-parametric procedure is demonstrated to be applicable to period and sequence effects, not just treatment effects.
- The BIOEQNEW program offers non-parametric point estimates and confidence intervals for various effects, including a non-parametric version of Schuirmann's two one-sided tests procedure.
Conclusions:
- Non-parametric analysis in bioequivalence studies can be extended beyond treatment effects to include period and sequence effects.
- The FORTRAN program BIOEQNEW provides a versatile tool for non-parametric analysis in bioequivalence and other studies.
- This extended non-parametric procedure serves as a valuable analogue to analysis of variance for two-period crossover designs.
Related Concept Videos
Crossover Experiments
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
Bioequivalence: Overview
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs
Bioequivalence studies: Biowaivers
Bioequivalence Data: Statistical Interpretation

