The current method for pooling the data from different batches or factors, suggested by ICH Q1E guidance, is to use analysis of covariance (ANCOVA) for test interaction between slopes and intercepts and factors. Failure to reject the null hypothesis of equality of slopes and equality of intercepts, however, does not prove that slopes and intercepts from different levels of factors are the same, and the data can be pooled for estimation of shelf life. In addition, the ANCOVA approach uses indirect parameters of intercepts and slopes in the regression model for assessment of poolability. The hypothesis for poolability is then formulated on the basis of the concept of equivalence for the means among the distributions of the quantitative attributes at a particular time point. Methods based on the intersection-union procedure are proposed to test the hypothesis of equivalence. A large simulation study was conducted to empirically investigate the size and power of the proposed method for the bracketing and matrixing designs given in the ICH QID guidance. Simulation results show that the proposed method can adequately control the size and provides sufficient power when the number of factors considered is fewer than three. A numerical example using the published data illustrates the proposed method.
