Missing observations in Youden square designs
Missing observations in Youden square designs
The reduction in efficiency in estimating treatment differences in Youden square designs from which individual observations have been lost is considered. A simple generalised inverse of the associated information matrix is used to develop expressions for the variances of the pairwise treatment comparisons. Results on the robustness of Youden squares to the loss of one or two observations are given, and it is shown that for two observations missing there are eight possible cases of resulting design which need to be considered. The frequencies of these cases depend on the form of the initial design, as well as on the design parameters. Examples of similar designs are used to illustrate these different frequencies of resulting designs.
balanced incomplete block designs, information matrix, generalised inverse, eigenvalues, pairwise variances of treatment differences
329-338
Mansson, Ralph A.
ae4c5cab-cfd5-4b27-81ae-be8e180cf81e
Prescott, Philip
cf0adfdd-989b-4f15-9e60-ef85eed817b2
2002
Mansson, Ralph A.
ae4c5cab-cfd5-4b27-81ae-be8e180cf81e
Prescott, Philip
cf0adfdd-989b-4f15-9e60-ef85eed817b2
Mansson, Ralph A. and Prescott, Philip
(2002)
Missing observations in Youden square designs.
Computational Statistics and Data Analysis, 40 (2), .
(doi:10.1016/S0167-9473(02)00009-9).
Abstract
The reduction in efficiency in estimating treatment differences in Youden square designs from which individual observations have been lost is considered. A simple generalised inverse of the associated information matrix is used to develop expressions for the variances of the pairwise treatment comparisons. Results on the robustness of Youden squares to the loss of one or two observations are given, and it is shown that for two observations missing there are eight possible cases of resulting design which need to be considered. The frequencies of these cases depend on the form of the initial design, as well as on the design parameters. Examples of similar designs are used to illustrate these different frequencies of resulting designs.
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Published date: 2002
Keywords:
balanced incomplete block designs, information matrix, generalised inverse, eigenvalues, pairwise variances of treatment differences
Organisations:
Statistics
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Local EPrints ID: 29991
URI: http://eprints.soton.ac.uk/id/eprint/29991
ISSN: 0167-9473
PURE UUID: 014824e3-e6db-4ac5-b805-cd3ac379e2e9
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Date deposited: 10 May 2006
Last modified: 15 Mar 2024 07:36
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Author:
Ralph A. Mansson
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