The Effect of Changing Scores for Multi-Way Tables with Open-Ended Ordered Categories
Yilmaz, Ayfer Ezgi
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Log-linear models are used to analyze the contingency tables. If the variables are ordinal or interval, because the score values affect both the model significance and parameter estimates, selection of score values has importance. Sometimes an interval variable contains open-ended categories as the first or last category. While the variable has open-ended classes, estimates of the lowermost and/or uppermost values of distribution must be handled carefully. In that case, the unknown values of the first and last classes can be estimated firstly, and then the score values can be calculated. In the previous studies, the unknown boundaries were estimated by using interquartile range (IQR). In this study, we suggested interdecile range (IDR), interpercentile range (IPR), and mid-distance range (MDR) as alternative to IQR to detect the effects of score values on model parameters.