| Summary: | 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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