Exploring series of multivariate censored temporal data through fuzzy coding and correspondence analysis
Pardoux, Catherine; Goldfarb, Bernard (2006), Exploring series of multivariate censored temporal data through fuzzy coding and correspondence analysis, Statistics in Medicine, 25, 10, p. 1741–1750. http://dx.doi.org/10.1002/sim.2305
Type
Article accepté pour publication ou publiéDate
2006Journal name
Statistics in MedicineVolume
25Number
10Publisher
Wiley
Pages
1741–1750
Publication identifier
Metadata
Show full item recordAbstract (EN)
We 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.Subjects / Keywords
paths in factorial mapping; multivariate temporal data; fuzzy coding; censoringRelated items
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