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

D. J. Best and J. C. W. Rayner

Journal of Applied Statistics, 2017, vol. 44, issue 1, 16-23

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.

Date: 2017
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DOI: 10.1080/02664763.2016.1158245

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