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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 劉仁沛 | |
dc.contributor.author | Shih-Yin Chen | en |
dc.contributor.author | 陳思穎 | zh_TW |
dc.date.accessioned | 2021-06-16T02:41:13Z | - |
dc.date.available | 2016-07-22 | |
dc.date.copyright | 2015-07-22 | |
dc.date.issued | 2015 | |
dc.date.submitted | 2015-07-22 | |
dc.identifier.citation | Altman D., Bland J.M. (1995) Absence of evidence is not evidence of absence. British Medical Journal, 311:485
Altman D., Bland J.M. (2004) Confidence intervals illuminate absence of evidence. British Medical Journal, 328:1016-1017 Brookes G., Barfoot P. (2014) GM crops: global socio-economic and environmental impacts 1996-2012. PG Economics Ltd, UK Chow S. C., Liu J. P. (2010) Design and Analysis of Bioavailability and Bioequivalence Studies, 3th Ed., CRC/Chapman and Hall, Taylor and France, New York. Chow S. C., Shao J., Wang H. (2003) Individual bioequivalence testing under 2x3 designs. Statistics in Medicine 2002; 21:629-648 Chu T. C. (2013). A Study on Applications of the Scaled Average Equivalence Test to Statistical Evaluation of Genetically Modified Products. Unpublished Master thesis, National Taiwan University Craig W., Tepfer M., Degrassi G., Ripandelli D. (2008) An Overview of General Features of Risk Assessments of Genetically Modified Crops. Euphytica, 2008; 164 (3): 853-880 European Food Safety Authority (EFSA) (2010). EFSA GMO Panel Opinion on Statistical Considerations for the Safety Evaluation of GMOs. European Food Safety Authority, Parma, Italy European Food Safety Authority (EFSA) (2001) Directive 2001/18/EC. European Food Safety Authority, Parma, Italy European Food Safety Authority (EFSA) (2010) EFSA GMO Panel Opinion on Statistical Considerations for the Safety Evaluation of GMOs. Presentation of the Full Statistical Code used for the Example. European Food Safety Authority, Parma, Italy European Agency for the Evaluation of Medicinal Products (EMEA). 2001. Note for guidance on the investigation of bioavailability and bioequivalence. Document CPMP/EWP/QWP/1401/98, European Agency for the Evaluation of Medicinal Products, Committee for Proprietary Medicinal Products, London, UK. Food and Drug Administration (FDA). (2001). Guidance for Industry - Statistical approaches to establishing bioequivalence. U.S. Department of Health and Human Services, Center for Drug Evaluation and Research. Food and Drug Administration, Rockville, Maryland, 2001. Hauck W. W., Anderson S. (1984). A new statistical procedure for testing equivalence in two-group comparative bioavailability trials. Journal of Pharmacokinetics and Pharmacodynamics; 12:83-91 Hyslop T., Hsuan F., Holder D.J. (2000). A small sample confidence interval approach to assess individual bioequivalence. Statistics in Medicine; 19:2885-2897 Hsu, J.C., Hwang, J.T.G., Liu, H.K., Ruberg, S.J. (1994) Confidence intervals associated with tests for bioequivalence. Biometrika, 81, 103-114. James C., (2014). Global Status of Commercialized Biotech/GM Crops: 2014. International Service for the Acquisition of Agri-biotech Applications (ISAAA) Brief No. 49. ISAAA: Ithaca, NY. Julious, S. A., McIntyre, N. E. (2012) Sample sizes for trials involving multiple correlated must-win comparisons. Pharmaceutical Statistics, 11 (2):177-85 Kenward M.G. and Roger J.H. (1997). Small sample inference for fixed effects from restricted maximum likelihood. Biometrics, 53: 983-997. Klumper W., Qaim M. (2014). A Meta-Analysis of the Impacts of Genetically Modified Crops. PLoS ONE 9(11): e111629. doi: 10.1371/journal.pone.0111629 Lee, A.F.S., Fineberg, N.S. (1991). A fitted test for the Behrens-Fisher problem. Communications in Statistics-Theory and Methods, 20, 653-666. Lee Y.H, Shao J., Chow S.C. (2004). Modified large-sample confidence intervals for linear combinations of variance components: extension, theory, and application. Journal of the American Statistical Association, 99, 467-478 Nicolia1 A., Manzo A., Veronesi1 F., Rosellini D. (2014). An Overview of the Last 10 Years of Genetically Engineered Crop Safety Research. Crit Rev Biotechnol, 2014; 34(1): 77–88 Patterson S.D., Jones B. (2012) Observations on scaled average bioequivalence. Pharmaceutical Statistics. 11,1-7 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: 657-680. World Health Organization (WHO) (2005) World Health Organization Draft Revision on Multisource (Generic) Pharmaceutical Products: Guidelines on Registration Requirements to Establish Interchangeability, Geneva, Switzerland. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/54129 | - |
dc.description.abstract | 根據歐盟委員會 (European Commission)的定義,生物體經由人為的基因轉植之後,使其擁有新的特性或性質者,稱為基因改造生物 (genetically modified organisms, GMOs)。現今,隨著基改作物的發展,基改作物的安全性評估成為一大重要議題。評估的內容包含基改作物的成分、基因型以及外表型。
歐盟食品安全管理局 (European Food Safety Authority, EFSA) 的基改作物委員會 (GMO Panel) 提出了針對基因改造作物安全性的統計考量評估方法。建議同時利用差異性檢定 (proof of difference) 以及對等性檢定 (proof of equivalence) 來進行評估,並建立其信賴區間 (confidence interval) 與對等性限度 (equivalence limit) 。 歐盟食品安全管理局 (European Food Safety Authority, EFSA) 對於基改作物的安全性評估之科學統計考量建議,基改作物與其傳統作物之平均差異值應落於商業品種之自然變異中以證明兩者間的生物相等性 (bioequivalence)。依據此準則,我們提出一項新的標準,亦即利用基改作物與其相對應之傳統作物的平均平方差異,與商業品種變異的比例,來進行基改作物安全性之對等性評估。此外,我們發現在真實資料中,商業品種變異之值時常很小,容易導致檢定結果過於保守,因此,我們給定商業品種變異之下限,取兩者之最大值作為檢定之尺度。 我們利用大樣本修正法 (Modified Large-Sample Method, MLS)進行變異數的估計,在混和效應的模式 (mixed-effects model) 之下建立線性化的95% 信賴上限,以此作為基改作物與其相對應傳統作物的安全性對等性評估之檢定方法。最後以一個例子介紹本方法之應用,並利用SAS進行模擬,以經驗型Ⅰ錯誤率和經驗檢定力來評估此一方法的效率。 | zh_TW |
dc.description.abstract | According to the European Commission, genetically modified organisms (GMOs) are organisms whose genetic characteristics are being modified artificially in order to give them a new desirable property. However, with the development of genetically modified organisms, the assessment of GMOs for safety is an important issue. The components, genotypes and phenotypes of GM plants should be identified and evaluated.
The Panel on GMOs of the European Food Safety Authority (EFSA) issued a guideline of Scientific Opinion on the Statistical Considerations for Safety Evaluation of GMOs in 2010. The GMO Panel of the EFSA indicated that both the proof of difference and the proof of equivalence are required for evaluation of the safety of GMOs. The EFSA’s scientific opinion on statistical considerations for the safety evaluation of GMOs suggests that the difference in average between the GM crop and its conventional counterpart should lie within the natural variability which can be estimated from the commercial varieties, in order to prove that the GMO crop is equivalent to its conventional counterpart. Therefore, we propose a new criterion for assessment of equivalence of the safety profile between the GM crop and conventional crop which is the scaled square mean difference between the GM crop and its conventional crop with the variance of commercial crops as the scaled factor. However, from the real data, we found that the variance of some commercial crops can be very small which would make the testing results too conservative. Thus, we propose to set a lower limit for the variance of commercial crops, and use the maximum value of two variances as the scaled factor. We applied the modified large-sample (MLS) method to estimate variance, and derive the 95% upper confidence limit of the linearized mixed-scaled criterion under the mixed-effects model. Then use this limit as the testing procedure for evaluation of equivalence in the safety profile between the GMO and its conventional crop. A numerical example illustrates the applications of the proposed method. A simulation was conducted with SAS to investigate the performance, in terms of size and power, for the proposed procedure. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T02:41:13Z (GMT). No. of bitstreams: 1 ntu-104-R02621205-1.pdf: 1931946 bytes, checksum: 98594b221056535485ac91781472a6b8 (MD5) Previous issue date: 2015 | en |
dc.description.tableofcontents | 口試委員會審定書...i
誌謝...ii 摘要...iii CONTENTS...vii LIST OF FIGURES...ix LIST OF TABLES...xi Chapter 1 Introduction...1 1.1 Definition and Introduction to Genetically Modified Organism...1 1.2 Global Status of GM Crops (ISAAA)...1 1.3 Controversies of Genetically Modified Crops...6 1.4 The Regulations of GMOs in the World...7 Chapter 2 Literature Review...14 2.1 Design of Field trials...14 2.2 Statistical Approaches by EFSA for GMOs...16 2.3 The Hypothesis for Differences Testing...18 2.4 Interpretation of Analysis by EFSA’s Approach...20 Chapter 3 Proposed Methods...29 3.1 The Criteria and Hypotheses...30 3.2 The Linear Statistical Model for Mixed-Effects Models...31 3.3 The Modified Large-Sample (MLS) Approach...34 3.4 The MLS Upper Confidence Bound...35 Chapter 4 Numeric Examples...43 4.1 Design of the Example...43 4.2 The 95% Upper Confidence Bound...44 Chapter 5 Simulation Study...56 5.1 Identification of Parameters for Simulation Designs...56 5.2 Simulation Results...57 5.2.1 Empirical Size...57 5.2.2 Empirical Power...58 Chapter 6 Discussion and Conclusion...91 References...96 Appendix...100 | |
dc.language.iso | en | |
dc.title | 以動差基礎標準統計評估基改作物之研究 | zh_TW |
dc.title | Statistical Evaluation of Equivalence of Genetic Modified Crops Based on the Moment-based Criteria | en |
dc.type | Thesis | |
dc.date.schoolyear | 103-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 林志榮,季瑋珠 | |
dc.subject.keyword | 基因改造作物,歐盟食品安全管理局,歐盟食品安全管理局,生物相等性,大樣本修正法,對等性限度,95%信賴上限, | zh_TW |
dc.subject.keyword | GMO,Genetically Modified crops,bioequivalence,European Food Safety Authority,Modified Large Sample Method,95% upper confidence limit, | en |
dc.relation.page | 113 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2015-07-22 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 農藝學研究所 | zh_TW |
顯示於系所單位: | 農藝學系 |
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