
doi: 10.1002/sim.2305
pmid: 16143983
AbstractWe present an exploratory analysis methodology for a multiple series of multivariate temporal data subject to censoring, and thus requiring the introduction of a coding technique: fuzzy coding preserving a large amount of the distributional information is fully adapted. Correspondence analysis is performed on the array produced by fuzzy coding. Projections of mean paths on factorial mappings, according to subgroup characteristics, highlight the behaviour of the underlying process. This approach is illustrated with an application to a randomized controlled clinical trial designed for comparing non‐diabetic chronic renal failure treatments. Our methodology has resulted in the identification of a difference between the treatments with an interpretation of the effects in subgroups of patients not obtainable with traditional survival methodology; it also provides some valuable insights for designing further studies on treatment of renal impairment. Copyright © 2005 John Wiley & Sons, Ltd.
Male, fuzzy coding, 610, Angiotensin-Converting Enzyme Inhibitors, multivariate temporal data, Probabilités et mathématiques appliquées, 519, censoring, Double-Blind Method, Fuzzy Logic, Creatinine, Data Interpretation, Statistical, Multivariate Analysis, Humans, Kidney Failure, Chronic, Multicenter Studies as Topic, Female, paths in factorial mapping, Randomized Controlled Trials as Topic
Male, fuzzy coding, 610, Angiotensin-Converting Enzyme Inhibitors, multivariate temporal data, Probabilités et mathématiques appliquées, 519, censoring, Double-Blind Method, Fuzzy Logic, Creatinine, Data Interpretation, Statistical, Multivariate Analysis, Humans, Kidney Failure, Chronic, Multicenter Studies as Topic, Female, paths in factorial mapping, Randomized Controlled Trials as Topic
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