Literature DB >> 17094347

Maximally selected chi-square statistics and binary splits of nominal variables.

Anne-Laure Boulesteix1.   

Abstract

We address the problem of maximally selected chi-square statistics in the case of a binary Y variable and a nominal X variable with several categories. The distribution of the maximally selected chi-square statistic has already been derived when the best cutpoint is chosen from a continuous or an ordinal X, but not when the best split is chosen from a nominal X. In this paper, we derive the exact distribution of the maximally selected chi-square statistic in this case using a combinatorial approach. Applications of the derived distribution to variable selection and hypothesis testing are discussed based on simulations. As an illustration, our method is applied to a birth data set.

Mesh:

Year:  2006        PMID: 17094347     DOI: 10.1002/bimj.200510191

Source DB:  PubMed          Journal:  Biom J        ISSN: 0323-3847            Impact factor:   2.207


  3 in total

1.  Rasch Trees: A New Method for Detecting Differential Item Functioning in the Rasch Model.

Authors:  Carolin Strobl; Julia Kopf; Achim Zeileis
Journal:  Psychometrika       Date:  2013-12-19       Impact factor: 2.500

Review 2.  The clinical utility of circulating tumour cells in patients with small cell lung cancer.

Authors:  Victoria Foy; Fabiola Fernandez-Gutierrez; Corinne Faivre-Finn; Caroline Dive; Fiona Blackhall
Journal:  Transl Lung Cancer Res       Date:  2017-08

3.  Bias in random forest variable importance measures: illustrations, sources and a solution.

Authors:  Carolin Strobl; Anne-Laure Boulesteix; Achim Zeileis; Torsten Hothorn
Journal:  BMC Bioinformatics       Date:  2007-01-25       Impact factor: 3.169

  3 in total

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