Abstract
AbstractApplication of a General Linear Model (GLM, “Analysis of Covariance”) to the statistical interpretation of stability data combines the methods of regression and analysis of variance in one common model. Expanding the well accepted method of linear regression upon time, the GLM model permits one to include supportive factors which may be either continuous regressors (temperature, humidity, etc.) or class effects (batch number, formulation type, manufacturer, etc.). Using the GLM procedure of SAS as a convenient software tool, the technique is illustrated by several examples. It is concluded that GLM provides a most suitable approach for the interpretation of stability data.
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