Een algemene methode tot leemtevulling

An exposition of the missing plot technique often applied in analysis of variance is given in very general terms.
Non-orthogonality mostly implies heavy computations. If the scheme of observations is almost orthogonal this technique, however, supplies in a simple way unbiassed and efficient estimates of the expectation values which occur in a linear hypothesis underlying an analysis of variance. Moreover the correct residual sum of squares required for a test or a confidence interval estimation is obtained without difficulty.
A correct test of an effect or an interaction will be provided by two estimates, the first under the null-hypothesis, the second under the alternative hypothesis. In the case of non-orthogonality this may imply two separate applications of the discussed technique. The difference between the two residual sums of squares will be used for the numerator of a valid F-criterion.
The technique is illustrated by an example.