A Method for Separation of Residual and Inetraction Effects in Cross Classifications.
NORTH CAROLINA UNIV CHAPEL HILL DEPT OF STATISTICS
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Consider a two-way cross-classification with factors R rows and C columns at r, c levels respectively and suppose that the expected value of an observation at the i-th level of R and the j-th level of C is represented in the form epsilon roh sub i kappa sub j rho kappa sub ij. The last term represents the interaction effect between R and C, usually denoted in the abbreviated form RxC. Variability about this expected value is represented by addition of a random variable with zero expected value. It is usually assumed that these random variables are mutually independent and have a common variance. If there is only one observation for each of the rc combinations of levels of R and C it is not possible to estimate the common variance separately from the interaction effects. author
- Statistics and Probability