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Scheffy's Confidence Intervals in the Models of Analysis of Covariance

✍ Scribed by M. Kuczyński; T. Drwièa

Publisher
John Wiley and Sons
Year
1985
Tongue
English
Weight
393 KB
Volume
27
Category
Article
ISSN
0323-3847

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✦ Synopsis

ScheffB'e confidence intervals for linear functions of some subvectors of a vector of parameters are prenented. The considered subvectors are such that covariance matrices of their estimators are known non-negative definite matrices multiplied by unknown positive constants. This property is cheracterintic of the least squares estimators of vectors of main and interaction effects in the analysis of covariance models of the following experimental deaigns: split-block, split-plot, completely randomized two-factor design and randomized complete block design.

The formulas for confidence intervals for linear functions of vectore of main or interaction effects in the designs mentioned above are given in the paper. The practical example is given as an illustration.

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