SAS for Linear Models, Fourth Edition

6.3.8 Empty Cells

Analyzing multifactor data with empty (or missing) cells often gives results of questionable value, since the data contain insufficient information to estimate the parameters of the model. (See Freund (1980) for a discussion of this problem.) The absence of data in one or more cells makes it very difficult to establish guidelines for imposing restrictions or generating appropriate estimable functions. PROC GLM helps investigate alternate estimable functions for such analyses, but no packaged program, including PROC GLM, provides a single best solution for all situations.

The problem of empty cells is illustrated by deleting the A=1, B=3 cell from the 2*3 factorial data in Output 6.7.

Table 6.6 gives the general form of estimable ...