### Abstract

The bioequivalence problem is of practical importance because the approval of most generic drugs in the United States and the European Community (EC) requires the establishment of bioequivalence between the brand-name drug and the proposed generic version. The problem is theoretically interesting because it has been recognized as one for which the desired inference, instead of the usual significant difference, is practical equivalence. The concept of intersection-union tests will be shown to clarify, simplify and unify bioequivalence testing. A test more powerful than the one currently specified by the FDA and EC guidelines will be derived. The claim that the bioequivalence problem defined in terms of the ratio of parameters is more difficult than the problem defined in terms of the difference of parameters will be refuted. The misconception that size-α bioequivalence tests generally correspond to 100(1 - 2α)% confidence sets will be shown to lead to incorrect statistical practices, and should be abandoned. Techniques for constructing 100(1 - α)% confidence sets that correspond to size-α bioequivalence tests will be described. Finally, multiparameter bioequivalence problems will be discussed.

Original language | English (US) |
---|---|

Pages (from-to) | 283-319 |

Number of pages | 37 |

Journal | Statistical Science |

Volume | 11 |

Issue number | 4 |

State | Published - 1996 |

Externally published | Yes |

### Fingerprint

### Keywords

- Bioavailability
- Bioequivalence
- Confidence interval
- Equivalence test
- Hypothesis test
- Intersection-union
- Level
- Pharmacokinetic
- Size
- Unbiased

### ASJC Scopus subject areas

- Mathematics(all)
- Statistics and Probability

### Cite this

*Statistical Science*,

*11*(4), 283-319.

**Bioequivalence trials, intersection-union tests and equivalence confidence sets.** / Berger, Roger L.; Hsu, Jason C.

Research output: Contribution to journal › Article

*Statistical Science*, vol. 11, no. 4, pp. 283-319.

}

TY - JOUR

T1 - Bioequivalence trials, intersection-union tests and equivalence confidence sets

AU - Berger, Roger L.

AU - Hsu, Jason C.

PY - 1996

Y1 - 1996

N2 - The bioequivalence problem is of practical importance because the approval of most generic drugs in the United States and the European Community (EC) requires the establishment of bioequivalence between the brand-name drug and the proposed generic version. The problem is theoretically interesting because it has been recognized as one for which the desired inference, instead of the usual significant difference, is practical equivalence. The concept of intersection-union tests will be shown to clarify, simplify and unify bioequivalence testing. A test more powerful than the one currently specified by the FDA and EC guidelines will be derived. The claim that the bioequivalence problem defined in terms of the ratio of parameters is more difficult than the problem defined in terms of the difference of parameters will be refuted. The misconception that size-α bioequivalence tests generally correspond to 100(1 - 2α)% confidence sets will be shown to lead to incorrect statistical practices, and should be abandoned. Techniques for constructing 100(1 - α)% confidence sets that correspond to size-α bioequivalence tests will be described. Finally, multiparameter bioequivalence problems will be discussed.

AB - The bioequivalence problem is of practical importance because the approval of most generic drugs in the United States and the European Community (EC) requires the establishment of bioequivalence between the brand-name drug and the proposed generic version. The problem is theoretically interesting because it has been recognized as one for which the desired inference, instead of the usual significant difference, is practical equivalence. The concept of intersection-union tests will be shown to clarify, simplify and unify bioequivalence testing. A test more powerful than the one currently specified by the FDA and EC guidelines will be derived. The claim that the bioequivalence problem defined in terms of the ratio of parameters is more difficult than the problem defined in terms of the difference of parameters will be refuted. The misconception that size-α bioequivalence tests generally correspond to 100(1 - 2α)% confidence sets will be shown to lead to incorrect statistical practices, and should be abandoned. Techniques for constructing 100(1 - α)% confidence sets that correspond to size-α bioequivalence tests will be described. Finally, multiparameter bioequivalence problems will be discussed.

KW - Bioavailability

KW - Bioequivalence

KW - Confidence interval

KW - Equivalence test

KW - Hypothesis test

KW - Intersection-union

KW - Level

KW - Pharmacokinetic

KW - Size

KW - Unbiased

UR - http://www.scopus.com/inward/record.url?scp=0043005476&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0043005476&partnerID=8YFLogxK

M3 - Article

VL - 11

SP - 283

EP - 319

JO - Statistical Science

JF - Statistical Science

SN - 0883-4237

IS - 4

ER -