Bayesian longitudinal models for paediatric kidney transplant recipients. Issue 3 (17th February 2016)

• Record Type: Journal Article
• Authors: Armero, C.; Forte, A.; Perpiñán, H.
• Is Part Of: Journal of applied statistics. Volume 43:Issue 3(2016)
• Page Start: 430
• Page End: 440
• Publication Date: 2016-02-17
• Subjects: hierarchical modelling -- linear mixed models -- repeated measures; 62F15 -- 62J05 -- 62P10; Statistics -- Periodicals; 519.5
• DOI: 10.1080/02664763.2015.1063117
• Languages: English
• ISSNs: 0266-4763

Abstract

Abstract : Chronic kidney disease is a progressive loss of renal function which results in the inability of the kidneys to properly filter waste from the blood. Renal function is usually estimated by the glomerular filtration rate (eGFR), which decreases with the worsening of the disease. Bayesian longitudinal models with covariates, random effects, serial correlation and measurement error are discussed to analyse the progression of eGFR in first transplanted children taken from a study in València, Spain.