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Bayesian longitudinal models for paediatric kidney transplant recipients

Author

Listed:
  • C. Armero
  • A. Forte
  • H. Perpiñán

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.

Suggested Citation

  • C. Armero & A. Forte & H. Perpiñán, 2016. "Bayesian longitudinal models for paediatric kidney transplant recipients," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(3), pages 430-440, March.
    • Handle: RePEc:taf:japsta:v:43:y:2016:i:3:p:430-440
    DOI: 10.1080/02664763.2015.1063117
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