Using negative binomial model to make inference about bioequivalence

• Main Authors: Hou,Yu-Ru, 侯玉汝
• Other Authors: Tsung-Shan Tsou
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/qv9fk4

碩士 === 國立中央大學 === 統計研究所 === 103 === Only when the two drugs pass the bioequivalence test, can we claim that two drugs are bioequivalent. Usually, the distribution of the pharmacokinetic data is assumed to be log-normal and inference is made under normality with logarithmically transformed data. The number of parameters in bivariate normal model makes it less convenient to make inference about bioequivalence. We propose using the bivariate negative binomial model to test for bioequivalence. We can convert the bivariate negative binomial likelihood to become robust to accommodate general pharmacokinetic data whose distribution might be less understood.