Phase II monitoring of binary response proles

In many situations, the quality of a process can be characterized betterby a relationship, known as a prole, between a response variable and one or morepredictors. almost all research eorts assume that response variable is continuous andfollows a normal distribution, while there are instances in which the response is a binaryvariable, and methods such as logistic regression are commonly used. in this paper,four control schemes namely hotelling t2, mewma, likelihood ratio test (lrt) andlrt/ewma are proposed to monitor binary response proles in phase ii. the performanceof the proposed control charts is evaluated and compared by simulation experiments fordierent shift values in the parameters of the prole in terms of the average run length(arl) criterion. the results show that all methods work well in the sense that they caneectively detect shifts in the process parameters. based on the results, mewma andlrt/ewma methods display a better performance for small to moderate and large shiftvalues, respectively.