Practical usage of O'Brien's OLS and GLS statistics in clinical trials

Multivariate techniques of O'Brien's OLS and GLS statistics are discussed in the context of their application in clinical trials. We introduce the concept of an operational effect size and illustrate its use to evaluate power. An extension describing how to handle covariates and missing data is developed in the context of Mixed models. This extension allowing adjustment for covariates is easily programmed in any statistical package including SAS. Monte Carlo simulation is used for a number of different sample sizes to compare the actual size and power of the tests based on O'Brien's OLS and GLS statistics.     

Sample size calculation for the Power Model for dose proportionality studies

There are several approaches to assess or demonstrate pharmacokinetic dose proportionality. One statistical method is the traditional ANOVA model, where dose proportionality is evaluated using the bioequivalence limits. A more informative method is the mixed effects Power Model, where dose proportionality is assessed using a decision rule for the estimated slope. Here we propose analytical derivations of sample sizes for various designs (including crossover, incomplete block and parallel group designs) to be analysed according to the Power Model.