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

Authors

Donald J. Best, University of NewcastleFollow
J. C. W Rayner, University of WollongongFollow

RIS ID

106224

Publication Details

Best, D. J. & Rayner, J. (2017). Analysis of ranked data in randomized blocks when there are missing values. Journal of Applied Statistics, 44 (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.