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

ABSTRACT

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.

KEYWORDS:

• Analysis of variance
• randomized block designs
• F tests
• powers
• ranks data
• test sizes

AMS SUBJECT CLASSIFICATION:

• 62Gxx
• 62Fxx

Acknowledgements

We acknowledge comments from two referees who helped produce a more focused paper.

Disclosure statement

No potential conflict of interest was reported by the authors.