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碩士 === 國立中央大學 === 統計研究所 === 102 === The thesis considers the bioequivalence (BE) test between the test drug and patent drug under a 2×2 crossover design. The bioavailability (BA) parameters under study are, for example, the overall drug concentration in blood (AUC) , the maximum drug concentration (...
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Online Access: | http://ndltd.ncl.edu.tw/handle/59622511354110993590 |
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ndltd-TW-102NCU053370092015-10-13T23:55:40Z http://ndltd.ncl.edu.tw/handle/59622511354110993590 none 偏斜常態分布下之生物對等性檢定 Chih-Yu Hsiao 蕭智宇 碩士 國立中央大學 統計研究所 102 The thesis considers the bioequivalence (BE) test between the test drug and patent drug under a 2×2 crossover design. The bioavailability (BA) parameters under study are, for example, the overall drug concentration in blood (AUC) , the maximum drug concentration (Cmax) , and the time to reach the maximum drug concentration. Note that the two one-sided tests (TOST) suggested by U.S. FDA that are constructed under the assumption of lognormal distribution for the estimated BA parameters may not be practical. Therefore, this article constructs a random effect model for the estimated BA parameters by assuming that the logarithm of the estimated BA is distributed according to a skew-normal distribution. The parameters of the random effect model are estimated by using the EM algorithm, a robust TOST is then conducted for the BE between the two drugs. A simulation study is implemented to investigate the type I error rate and power of the two different BE tests. The result show that the two BE tests are similar on holding their type I error rates, but the robust BE test has a better power performance than the conventional TOST. Finally, analyze a real data set is illustrated to demonstrate the application of the proposed random effect model and the bioequivalence test. Yuh-Ing Chen 陳玉英 2014 學位論文 ; thesis 35 zh-TW |
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碩士 === 國立中央大學 === 統計研究所 === 102 === The thesis considers the bioequivalence (BE) test between the test drug and patent drug under a 2×2 crossover design. The bioavailability (BA) parameters under study are, for example, the overall drug concentration in blood (AUC) , the maximum drug concentration (Cmax) , and the time to reach the maximum drug concentration. Note that the two one-sided tests (TOST) suggested by U.S. FDA that are constructed under the assumption of lognormal distribution for the estimated BA parameters may not be practical. Therefore, this article constructs a random effect model for the estimated BA parameters by assuming that the logarithm of the estimated BA is distributed according to a skew-normal distribution. The parameters of the random effect model are estimated by using the EM algorithm, a robust TOST is then conducted for the BE between the two drugs. A simulation study is implemented to investigate the type I error rate and power of the two different BE tests. The result show that the two BE tests are similar on holding their type I error rates, but the robust BE test has a better power performance than the conventional TOST. Finally, analyze a real data set is illustrated to demonstrate the application of the proposed random effect model and the bioequivalence test.
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Yuh-Ing Chen |
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Yuh-Ing Chen Chih-Yu Hsiao 蕭智宇 |
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Chih-Yu Hsiao 蕭智宇 |
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Chih-Yu Hsiao 蕭智宇 none |
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Chih-Yu Hsiao |
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2014 |
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http://ndltd.ncl.edu.tw/handle/59622511354110993590 |
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AT chihyuhsiao none AT xiāozhìyǔ none AT chihyuhsiao piānxiéchángtàifēnbùxiàzhīshēngwùduìděngxìngjiǎndìng AT xiāozhìyǔ piānxiéchángtàifēnbùxiàzhīshēngwùduìděngxìngjiǎndìng |
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1718087981916487680 |