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系統識別號 U0026-0812200911272270
論文名稱(中文) 利用改進Anderson-Hauck方法評估平均生體相等性之研究
論文名稱(英文) The Evaluation of Average Bioequivalence Using a Modified Anderson-Hauck’s Test
校院名稱 成功大學
系所名稱(中) 統計學系碩博士班
系所名稱(英) Department of Statistics
學年度 93
學期 2
出版年 94
研究生(中文) 陳韋翰
研究生(英文) Wei-Hang Chen
電子信箱 weibowei@gmail.com
學號 r2692405
學位類別 碩士
語文別 英文
論文頁數 159頁
口試委員 口試委員-陳占平
指導教授-馬瀰嘉
口試委員-溫淑惠
指導教授-劉仁沛
中文關鍵字 生體相等性  拔靴法  模擬研究  經驗檢定力  經驗型I誤 
英文關鍵字 average bioequivalence  empirical power  simulation  size  two-sequence and two-period crossover design 
學科別分類
中文摘要 新藥又稱作(原廠藥)的研發平均需花10~12年的時間和八百億美元,因此新藥的研發是非常耗時又需花費巨大金額,為反映成本和賺取利潤,通常新藥的價格非常昂貴,於是政府為了降低藥物價格,同意原研發藥廠等到專利期滿,一般藥廠就可仿照原廠藥製造出具相同療效的藥又稱作(學名藥),在1984年美國食品與藥物管理局(FDA)准許學名藥上市,只須証明學名藥與原廠藥是否具有平均生體相等性( bioequivalence)即可,因為學名藥不須長期的臨床試驗,故學名藥廠可以節省大量的金錢和研發時間。
目前,針對於評估平均生體相等性,FDA建議採用一兩序列兩期重複的交叉試驗設計,而評估平均生體相等性是一種區間假設檢定,有許多學者提出不同的方法來評定,此種區間假設檢定包括Schuirmann提出的合併單邊檢定方法(Schuirmann’s Two One-Sided Tests),及Anderson和Hauck提出的方法(Anderson and Hauck’s Test)以及許多貝氏估計方法。基於Anderson 和 Hauck方法下,本文透過拔靴重複抽樣法(Bootstrap Resampling Methods)提出一個模擬研究,改善原來方法中對於非中心參數估計的盲點,也比較許多不同方法和非常態分配假設下,在型I誤差的機率和檢定力的優劣。



英文摘要 Only after the patent of a brand-name innovative drug product is expired, its generic copies are allowed to market. However, regulatory approval requires evidence of bioequivalence based on the pharmacokinetic responses derived from the time-plasma concentration curve of the active ingredients. Currently, about the evaluation of interval hypotheses testing of average bioequivalence, Schuirmann’s two one-sided tests and Anderson and Hauck’s test would be introduced.
However, there exists some problem within the Anderson and Hauck’s test. It need to calculate the noncentrality parameter in test statistics. The Bootstrap resampling method is introduced to perform the empirical distribution. The real test statistics distribution is performed by a simulation study on the various combinations of parameters and sample size under 2 2 crossover design. The simulation study was conducted to empirically examine and compare the size and power of the original test and our proposed four methods. In the simulation study, we also recommend exponential distribution, uniform distribution and Cauchy distribution to replace with the normal distribution.



論文目次 Contents
Chapter 1 Introduction 1
1.1 What are Generic Drugs 1
1.2 Average Bioequivalence (ABE) 2
1.3 Design and Current Methods for ABE 3
1.3.1 Two-sequence and Two-period Crossover Design 3
1.3.2 Current Methods for assessment of ABE 4

Chapter 2 Literature Review 6
2.1 Statistical Methods for the Average Bioequivalence (ABE) 6
2.2 Interval Hypothesis 11
2.3 Confidence Interval 12
2.3.1 The Confidence Interval Approach 12
2.3.2 The Classical (Shortest) Confidence Interval 14
2.4 Testing Procedure 15
2.4.1 Schuirmann’s Two One-Sided Tests Procedure 15
2.4.2 Anderson and Hauck’s Test 16
2.5 Bootstrap Resampling Method 19
2.5.1 The Concept of Bootstrap resampling 20

Chapter 3 Proposed Testing Procedure 23
3.1 Method based on the Modified Anderson-Hauck’s test 24
3.2 Method Based on the Directed Difference 26
3.3 The Bootstrap Procedure of Schuirmann’s Test 27
3.4 The Method Based on the Bootstrap Empirical Distribution 28

Chapter 4 Simulation Studies 32
4.1 The Simulation Processes 32
4.2 Simulation Results 38
4.2.1 Binormal model 38
4.2.2 Exponential model 41
4.2.3 Uniform model 45
4.2.4 Cauchy model 48
Chapter 5 A Numerical Example 53

Chapter 6 Conclusion and Discussion 60

References 62
Appendix A 66
Appendix B 102
Appendix C 151

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