دراسـة مقارنة لتقـدير القيـم المفقودة في تصميــم المــربع اللاتينـي باستخـدام طريقـتي يتـس وهاري

Abstract

Four methods for tackling missing values in Latin square design have been presented: Yates, Harry, Rubin, and the method of Haseman and Gaylar. To make preference among these methods some statistical measurements have been used, which are: lowest value of the mean square error (MSe), highest value of the mean square treatments (MSt) and the value of significant differences between treatments (F cal.). The easiest path of statistical analysis has been taken into account. It has been found that the most preferable method is Yates' method which has the most complicated application whenever the number of missing values are increased, followed by Harry method which has a moderate application difficulty, then Haseman and Gaylar method, and finally Rubin method. The last two methods have the easiest applications.