Order-Restricted Inference with Linear Rank Statistics in Microarray Data

- Journal title : Korean Journal of Applied Statistics
- Volume 24, Issue 1, 2011, pp.137-143
- Publisher : The Korean Statistical Society
- DOI : 10.5351/KJAS.2011.24.1.137

Title & Authors

Order-Restricted Inference with Linear Rank Statistics in Microarray Data

Kang, Moon-Su;

Kang, Moon-Su;

Abstract

The classification of subjects with unknown distribution in a small sample size often involves order-restricted constraints in multivariate parameter setups. Those problems make the optimality of a conventional likelihood ratio based statistical inferences not feasible. Fortunately, Roy (1953) introduced union-intersection principle(UIP) which provides an alternative avenue. Multivariate linear rank statistics along with that principle, yield a considerably appropriate robust testing procedure. Furthermore, conditionally distribution-free test based upon exact permutation theory is used to generate p-values, even in a small sample. Applications of this method are illustrated in a real microarray data example (Lobenhofer et al., 2002).

Keywords

Microarray;union-intersection principle;linear rank statistics;permutation;

Language

English

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