A Study on Applications of the Scaled Average Equivalence Test to Statistical Evaluation of Genetically Modified Products

• Main Authors: Ting-Chen Chu, 朱亭甄
• Other Authors: 劉仁沛
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/16359712355330993214

碩士 === 國立臺灣大學 === 農藝學研究所 === 101 === According to the European Commission, genetically modified organisms (GMOs) are organisms, such as plants and animals, whose genetic characteristics are being modified artificially in order to give them a new property. However, with the development of genetically modified organisms, the assessment of GMOs for safety is an important issue. The components, genotype and phenotype 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 suggests that the difference in average between the GM crop and its conventional counterpart lie within the natural variability which can be estimated from the commercial varieties. 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. Under the mixed-effects model, we applied the modified large-sample (MLS) method to derive the 95% upper confidence limit of the linearized criterion as the testing procedure for evaluation of equivalence in the safety profile between the GMO and its conventional crop. A simulation was conducted to investigate the performance, in terms of size and power, for the proposed procedure. A numerical example illustrates the applications of the proposed method.