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.