A Two - Way Analysis of Covariance Model for Classi cation ofStability Data

This paper proposes a procedure for testing and classifying stability data with multiple factors. A two-way analysis of covariance is used to classify the diierences among the batches as well as another factor such as package type and/or product strength. In the test procedure, slopes and intercepts of the main eeects are tested using a combination of simultaneous and sequential F-tests. Based on the test procedure results, the data are classiied into one of four diierent groups. For each group, shelf life can be calculated accordingly. We examine if the procedure produces satisfactory control of the probability of a Type I error and the power of detecting the diierence of degradation rates and intercepts for diierent nominal levels. The method is evaluated with a Monte Carlo simulation study. The proposed procedure is compared with the current FDA procedure using real data. The views expressed in this paper are those of authors and not necessarily of the Food and Drug Administration.