Analysis of ranked data in randomized blocks when there are missing values

Data consisting of ranks within blocks are considered for randomized block designs when there are missing values. Tied ranks are possible. Such data can be analysed using the Skillings-Mack test. Here we suggest a new approach based on carrying out an ANOVA on the ranks using the general linear mode...

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Published in:Journal of applied statistics 2017-01, Vol.44 (1), p.16-23
Main Authors: Best, D. J., Rayner, J. C. W.
Format: Article
Language:English
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62Fxx
62Gxx
Analysis of variance
Applied statistics
Design analysis
Economic models
F tests
Mathematical models
Packages
Platforms
powers
randomized block designs
ranks data
test sizes
Variance analysis
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description Data consisting of ranks within blocks are considered for randomized block designs when there are missing values. Tied ranks are possible. Such data can be analysed using the Skillings-Mack test. Here we suggest a new approach based on carrying out an ANOVA on the ranks using the general linear model platform available in many statistical packages. Such a platform allows an ANOVA to be calculated when there are missing values. Indicative sizes and powers show the ANOVA approach performs better than the Skillings-Mack test.
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subjects 62Fxx
62Gxx
Analysis of variance
Applied statistics
Design analysis
Economic models
F tests
Mathematical models
Packages
Platforms
powers
randomized block designs
ranks data
test sizes
Variance analysis
title Analysis of ranked data in randomized blocks when there are missing values
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