Keywords: Equivalence tests, Wald tests, constrained maximum likelihood estimate, Exact-based test, GPQ, Analytical Biosimilarity
For the reference scaled equivalence hypothesis, Chen et al. (2017) proposed to use the Wald test with Constrained Maximum Likelihood Estimate (CMLE) of the standard error to improve the efficiency when the numbers of lots for both test and reference products are small and variances are unequal. However, by using the Wald test with CMLE standard error (Chen et al., 2017), simulations show that the type I error rate is below the nominal significance level. Weng et al. (2017) proposed the Modified Wald test with CMLE standard error by replacing the maximum likelihood estimate of reference standard deviation with the sample estimate (MWCMLE), resulting in further improvement of type I error rate and power over the tests proposed in Chen et al. (2017). In this presentation, we further compare the proposed method to the exact-test-based method (Dong et al., 2017a) and the Generalized Pivotal Quantity (GPQ) method (Weerahandi, 1993) with equal or unequal variance ratios or equal or unequal numbers of lots for both products. The simulations show that the proposed MWCMLE method outperforms the other two methods in type I error rate control and power improvement.