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Multiple Tests for Different Sets of Variables Using a Data‐Driven Ordering of Hypotheses, with an Application to Gene Expression Data
Author(s) -
Kropf S.,
Läuter J.
Publication year - 2002
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/1521-4036(200210)44:7<789::aid-bimj789>3.0.co;2-#
Subject(s) - expression (computer science) , gene expression , statistics , computational biology , statistical hypothesis testing , computer science , gene , data mining , mathematics , biology , econometrics , genetics , programming language
A multiple parametric test procedure is proposed, which considers tests of means of several variables. The single variables or subsets of variables are ordered according to a data‐dependent criterion and tested in this succession without alpha‐adjustment until the first non‐significant test. The test procedure needs the assumption of a multivariate normal distribution and utilizes the theory of spherical distributions. The basic version is particularly suited for variables with approximately equal variances. As a typical example, the procedure is applied to gene expression data from a commercial array.