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Abstract
This paper presents a new method for the analysis of variance of multiple classifications with unequal subclass numbers. It is believed that the method is simpler and more expeditious than the standard method of fitting constants. The process of adjusting is accomplished by substituting in the following equation:
where 
is the mean of the
i
th subclass in the jth row or column, 
is the mean of the
i
th row or column, 
is the grand mean and 
is the adjusted mean of the
i
th subclass in the
i
th row or column.
The method is based upon the assumption that the weighted sum of squares of the subclass means that are adjusted for the border mean effects is an efficient estimate of the variance due to interaction. Justification of this assumption is indicated by the fact that the difference between the differences of subclass means for a given classification is unchanged by the adjusting process. It is further demonstrated that if a sufficient number of adjustings are carried out the results will be the same as those obtained by the method of fitting constants.