Phase II monitoring of binary response pro les

In many situations, the quality of a process can be characterized better by a relationship, known as a prole, between a response variable and one or more predictors. Almost all research eorts assume that response variable is continuous and follows a normal distribution, while there are instances in which the response is a binary variable, and methods such as logistic regression are commonly used. In this paper, four control schemes namely Hotelling T2, MEWMA, Likelihood Ratio Test (LRT) and LRT/EWMA are proposed to monitor binary response proles in phase II. The performance of the proposed control charts is evaluated and compared by simulation experiments for dierent shift values in the parameters of the prole in terms of the Average Run Length (ARL) criterion. The results show that all methods work well in the sense that they can eectively detect shifts in the process parameters. Based on the results, MEWMA and LRT/EWMA methods display a better performance for small to moderate and large shift values, respectively.