Bayesian joint modeling for assessing the progression of chronic kidney disease in children

Statistical Methods in Medical Research

Volumn 27, Issue 1, 2018, Pages 298-311

  Armero, Carmen ^a   Forte, Anabel ^a   Perpiñán, Hèctor ^a,b   Sanahuja, María José ^c   Agustí, Silvia ^c  

^a UNIVERSITY OF VALENCIA   (Spain)

^b Vaccine Research   (Spain)

^c Foundation for the Promotion of Health and Biomedical Research of Valencia Region   (Spain)

Author keywords

Competing risks; Left truncation; Longitudinal data; Non ignorable dropout; Random effect joint models

Indexed keywords

ARTICLE; BAYES THEOREM; CALCULATION; CHILD; CHILDHOOD; CHRONIC KIDNEY FAILURE; DISEASE COURSE; ESTIMATED GLOMERULAR FILTRATION RATE; HUMAN; MATHEMATICAL MODEL; PREDICTION; STATISTICAL MODEL; SURVIVAL; DISEASE EXACERBATION; PATHOLOGY; PRESCHOOL CHILD; SURVIVAL ANALYSIS;

BAYES THEOREM; CHILD; CHILD, PRESCHOOL; DISEASE PROGRESSION; HUMANS; RENAL INSUFFICIENCY, CHRONIC; SURVIVAL ANALYSIS;

EID: 85041385408     PISSN: 09622802     EISSN: 14770334     Source Type: Journal    
DOI: 10.1177/0962280216628560     Document Type: Article

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