1963
DOI: 10.2307/1266494
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Programming Univariate and Multivariate Analysis of Variance

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Cited by 55 publications
(39 citation statements)
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“…In such a case, the SEX effect would be determined as before but the DRUG-within-SEX effect would correspond to a coalescing of what before were the DRUG and SEX × DRUG sources of variation. The term "interaction" has no meaning for exclusively nested designs; general effects for hierarchical factors after the first may always be obtained com putationally by a pooling of what, for factorial designs, would be main effects and certain interactions (see Bock, 1963). Design textbooks like Winer's (1962) should be studied for further details relating to interpreta tions of nested designs.…”
Section: ™3(r)se(r)mentioning
confidence: 99%
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“…In such a case, the SEX effect would be determined as before but the DRUG-within-SEX effect would correspond to a coalescing of what before were the DRUG and SEX × DRUG sources of variation. The term "interaction" has no meaning for exclusively nested designs; general effects for hierarchical factors after the first may always be obtained com putationally by a pooling of what, for factorial designs, would be main effects and certain interactions (see Bock, 1963). Design textbooks like Winer's (1962) should be studied for further details relating to interpreta tions of nested designs.…”
Section: ™3(r)se(r)mentioning
confidence: 99%
“…However, Bock (1963) presented a more elegant procedure to deal with the case where whole-vectors are missing. His approach can be explained with reference to Equations 4 and 12.…”
Section: Y=xb + Ementioning
confidence: 99%
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“…e is a vector of random components with mean vector 0 and variance-covariance matrix I. The model matrix W can he specified by an n-fold Kronecker product of a 2 x2 basis matrix (Bock, 1963), for instance, as follows, where the operator "x" indicates Kronecker product, and c is a scalar constant. Since the scale unit c is absorbed in the values of fi, the value of c does not affect the results of the present study.…”
Section: Factorial Model For Logarithmic Contrastsmentioning
confidence: 99%
“…There are general least-squares programs capable of reduced-model tests [e.g., SAS's GLM (Barr et al, 1976); Bock, 1965;BMDX63/11V (Dixon, 1973);Finn, 1972;Woodward & Overall, 1974]. These are not labeled as canonical correlation programs, since they work with sums of squares and cross-products (SP) matrices, rather than with correlation matrices; the procedures are nevertheless equivalent.…”
mentioning
confidence: 99%