Although there are many procedures developed for handling multiple outcomes comparison in the literature, the nonparametric methodology for group comparison with covariate adjustment is still in its infancy. One can use rank-sum test, adjusted rank-sum test, or max-type test by analyzing the processed data orthogonal to the space spanned by covariates. However, the power is not satisfactory. In this work, we combine the adjusted rank-sum test and pseudo F test and then construct a MIN2 test to handle this issue. The performances of MIN2 are thoroughly explored by extensive computer simulations and a real example.
ZHANG Shenghu
,
ZHU Jiayan
,
ZHANG Sanguo
. A powerful procedure for multiple outcomes comparison with covariate adjustment and its application to genomic data[J]. Journal of University of Chinese Academy of Sciences, 2019
, 36(2)
: 155
-161
.
DOI: 10.7523/j.issn.2095-6134.2019.02.002
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