Numerical methods for the evaluation of individual bioequivalence criteria

The evaluation of individual bioequivalence (IBE) by bootstrap resampling u sing common statistical software, for example SAS, is extremely time consum ing. In this article, an estimation procedure that can be implemented in a high level language with the same degree of accuracy as SAS is described. T he necessary parameter estimating equations under both least square (LSE) a nd restricted maximum likelihood (REML) methods are given. The algorithms u sed to numerically compute these values are outlined and tested in FORTRAN, on several simulated data sets and shown to reproduce SAS results with at least 10(-3) precision. More importantly, the REML bootstrap algorithm redu ces the time taken in SAS by a factor of 20. Secondary results indicate tha t LSE and REML parameter estimates are similar for mild unbalancedness. PRO C MIXED, with unstructured (UN) and compound symmetry heterogeneous (CSH) v ariance structures give the same results except when the subject-by-treatme nt interaction variance, sigma(D)(2), is 0 in which case CSH significantly overestimates sigma(D)(2) and underestimates the within-treatment variances . It is concluded that bootstrap evaluation of IBE is efficiently done usin g either the LSE or REML algorithm in FORTRAN. Copyright (C) 2000 John Wile y & Sons, Ltd.