เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| การวิเคราะห์ชีวสมมูล (การทดสอบด้านเดียวสองครั้ง)× | การทดสอบสมมูล (TOST× | |
|---|---|---|
| สาขาวิชา≠ | เภสัชมิติ | สถิติศาสตร์ |
| ตระกูล | Hypothesis test | Hypothesis test |
| ปีกำเนิด | 1987 | 1987 |
| ผู้ริเริ่ม | Donald J. Schuirmann | Donald J. Schuirmann |
| ประเภท | Parametric equivalence test | Parametric equivalence test |
| แหล่งต้นตำรับ≠ | Schuirmann, D. J. (1987). A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability. Journal of Pharmacokinetics and Biopharmaceutics, 15(6), 657–680. DOI ↗ | Schuirmann, D.J. (1987). A Comparison of the Two One-Sided Tests Procedure and the Power Approach for Assessing the Equivalence of Average Bioavailability. Journal of Pharmacokinetics and Biopharmaceutics, 15(6), 657–680. DOI ↗ |
| ชื่อเรียกอื่น | TOST Procedure, Average Bioequivalence, BE Analysis, Biyoeşdeğerlik Analizi | TOST, two one-sided tests, bioequivalence test, Eşdeğerlik Testi (TOST — Two One-Sided Tests) |
| ที่เกี่ยวข้อง≠ | 2 | 5 |
| สรุป≠ | Bioequivalence Analysis is a regulatory-grade statistical framework used to determine whether a test drug formulation (generic or reformulated) delivers the active ingredient to the systemic circulation at a rate and extent comparable to a reference product. Introduced by Donald J. Schuirmann in 1987, the method operationalizes equivalence through the Two One-Sided Tests (TOST) procedure, replacing the ambiguous absence-of-difference paradigm with an explicit equivalence margin evaluated on log-transformed pharmacokinetic endpoints such as AUC and C_max. | The equivalence test using the Two One-Sided Tests (TOST) procedure is a parametric hypothesis test designed to demonstrate that the difference between two group means falls within a pre-specified equivalence region ±Δ. Introduced by Schuirmann (1987) in the context of pharmaceutical bioequivalence, TOST reverses the logic of classical null-hypothesis testing: instead of trying to detect a difference, it provides positive evidence of similarity. |
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