A General Recursive Procedure for Analysis of Variance

Wilkinson, G. N.

doi:10.2307/2334933

Cited by 12 publications

(12 citation statements)

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“…Wilkinson (1970) proposed a method of wide application for the analysis of experimental data. If there are no effects confounded in the interblock analysis, as, for example, with a balanced incomplete block design, fQ0 is found by putting the ith element of t, equal to 1/ri and the rest equal to zero (i = 1, ..., v).…”

Section: Relevance To the Methods Of Kijiper And Corstenmentioning

confidence: 99%

The Basic Contrasts of an Experimental Design with Special Reference to the Analysis of Data

Pearce¹,

Calinski²,

Marshall³

1974

Biometrika

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JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. Biometrika Trust is collaborating with JSTOR to digitize, preserve and extend access to Biometrika. SUMMARYThe least squares solution for a block design is considered in some detail for both the intrablock and the interblock cases. It leads to the identification of certain contrasts, here called basic, that are estimated independently and with efficiency factors that are readily determined. Basic contrasts indicate possible partitions of the treatment sum of squares and aid in the computation of the appropriate analysis of variance. Also they help to clarify the relationship between three methods of computing the analysis for the general case of block designs, namely those of (i) Tocher, (ii) Kuiper and Corsten and (iii) Wilkinson.

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Section: Relevance To the Methods Of Kijiper And Corstenmentioning

confidence: 99%

The Basic Contrasts of an Experimental Design with Special Reference to the Analysis of Data

Pearce¹,

Calinski²,

Marshall³

1974

Biometrika

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“…These papers gave symbolic mixed models and skeleton‐ANOVA tables for the examples. Brien (1979c) extended Wilkinson () to produce an algorithm for computing the ANOVA for data from a multitiered experiment in which the designs in both phases are nonorthogonal. Houtman & Speed , section 5.5) noted that, as a class, two‐phase experiments do not satisfy general balance.…”

Section: Some Historymentioning

confidence: 99%

Multiphase experiments in practice: A look back

Brien

2017

Aus NZ J of Statistics

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Summary Multiphase experiments are introduced and an overview of their design and analysis as it is currently practised is given via an account of their development since 1955 and a literature survey. Methods that are available for designing and analysing them are outlined, with an emphasis on making explicit the role of the model in their design. The availability of software and its use is described in detail. Overall, while multiphase designs have been applied in areas such as plant breeding, plant pathology, greenhouse experimentation, product storage, gene expression studies, and sensory evaluation, their deployment has been limited.

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“…The above equation forms the basis of an algorithm due to Wilkinson (1970) for fitting analysis of variance models by regression methods. The steps are…”

Section: Least Squares Estimationmentioning

confidence: 99%

The Linear Model and Hypothesis

Seber

2015

Springer Series in Statistics

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A General Recursive Procedure for Analysis of Variance

Cited by 12 publications

References 0 publications

The Basic Contrasts of an Experimental Design with Special Reference to the Analysis of Data

The Basic Contrasts of an Experimental Design with Special Reference to the Analysis of Data

Multiphase experiments in practice: A look back

The Linear Model and Hypothesis

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