Nonparametric Rank-Based Test Procedures for Non-Additive Models in the Two-Way Layout I. No Replication

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One of the major unresolved problems in the area of nonparametric statistics is the need for satisfactory rank-based test procedures for non-additive models in the two-way layout, especially when there is only one observation each combination of the levels of the experimental factors. In this paper we consider an arbitrary non-additive model for the two-way layout with n levels of each factor. We utilize both alignment and ranking of the data together with basic properties of Latin squares to develop rank tests for interaction (non-additivity). Our technique involves first aligning with one of the main effects, ranking within the other main effects (columns and rows) and then adding the resulting ranks within "interaction bands" corresponding to orthogonal partitions of the interaction for the model, as denoted by the letters of an n x n Latin square. A Friedman-type statistic is then computed on the resulting sums. This is repeated for each of (n-1) mutually orthogonal Latin squares (thus accounting for all the interaction degrees of freedom). The resulting (n-1) Friedman-type statistics are finally combined to obtain an overall test statistic. The necessary null distribution tables for applying the proposed test for non-additivity are presented and we discuss the results of a Monte Carlo simulation study of the relative powers of this new procedure and other (parametric and nonparametric) procedures designed to detect interaction in a two-way layout with one observation per cell.


Communications in Statistics - Theory and Methods





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