Combining several ordinal measures in clinical studies.
In medical research, it is rare that a single variable is sufficient to represent all relevant aspects of epidemiological risk, genomic activity, adverse events, or clinical response. Since biological systems tend to be neither linear, nor hierarchical in nature, the assumptions of traditional multivariate statistical methods based on the linear model can often not be justified on theoretical grounds. Establishing concept validity through empirical validation is not only problematic, but also time consuming. This paper proposes the use of u-statistics for scoring multivariate ordinal data and a family of simple non-parametric tests for analysis. The scoring method is demonstrated to be applicable to scoring clinical response profiles in the treatment of psoriasis and then to identifying genomic pathways that best correlate with these profiles.
Wittkowski
Knut M
KM
General Clinical Research Center, The Rockefeller University, New York, NY 10021, USA. kmw@rockefeller.edu
Lee
Edmund
E
Nussbaum
Rachel
R
Chamian
Francesca N
FN
Krueger
James G
JG
D000276:Adjuvants, Immunologic / Q000627:therapeutic use; D002986:Clinical Trials as Topic / Q000379:methods*; D016207:Cytokines / Q000235:genetics / Q000276:immunology; D003627:Data Interpretation, Statistical; D006801:Humans; D015999:Multivariate Analysis; D011565:Psoriasis / Q000188:drug therapy / Q000276:immunology; D012333:RNA, Messenger / Q000737:chemistry / Q000235:genetics; D012107:Research Design; D020133:Reverse Transcriptase Polymerase Chain Reaction; D013223:Statistics as Topic / Q000379:methods*; D018709:Statistics, Nonparametric
D000276:Adjuvants, Immunologic; D016207:Cytokines; D012333:RNA, Messenger