Bayesian nonparametric mixed-effects joint model for longitudinal-competing risks data analysis in presence of multiple data features

Statistical Methods in Medical Research

Volumn 26, Issue 5, 2017, Pages 2407-2423

  Lu, Tao ^a  

^a STATE UNIVERSITY OF NEW YORK   (United States)

Author keywords

AIDS study; Bayesian inference; competing risk; detection limit; longitudinal data; measurement error; mixed effects models; skew distribution; survival data; varying coefficient hazard models

Indexed keywords

ACCURACY; ACQUIRED IMMUNE DEFICIENCY SYNDROME; ALGORITHM; ARTICLE; BAYES THEOREM; CD4 LYMPHOCYTE COUNT; DATA ANALYSIS; HISTOGRAM; HUMAN; LIMIT OF DETECTION; MEASUREMENT ERROR; NUCLEOTIDE SEQUENCE; RELIABILITY; RISK ASSESSMENT; SURVIVAL RATE; VIRUS LOAD; DRUG EFFECT; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; LONGITUDINAL STUDY; MALE; NONPARAMETRIC TEST; PROPORTIONAL HAZARDS MODEL; RISK FACTOR; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; SURVIVAL ANALYSIS; TREATMENT OUTCOME; VIROLOGY;

ANTI HUMAN IMMUNODEFICIENCY VIRUS AGENT;

ANTI-HIV AGENTS; BAYES THEOREM; CD4 LYMPHOCYTE COUNT; DATA INTERPRETATION, STATISTICAL; HIV INFECTIONS; HUMANS; LONGITUDINAL STUDIES; MALE; MODELS, STATISTICAL; PROPORTIONAL HAZARDS MODELS; RISK FACTORS; STATISTICS, NONPARAMETRIC; SURVIVAL ANALYSIS; TREATMENT OUTCOME; VIRAL LOAD;

EID: 85031694458     PISSN: 09622802     EISSN: 14770334     Source Type: Journal    
DOI: 10.1177/0962280215597939     Document Type: Article

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