Bayesian inference in semiparametric mixed models for longitudinal data

Biometrics

Volumn 66, Issue 1, 2010, Pages 70-78

  Li, Yisheng ^a   Lin, Xihong ^b   Müller, Peter ^a  

^a UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

^b HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

Dirichlet process prior; Identifiability; Postprocessing; Random effects; Smoothing spline; Uniform shrinkage prior; Variance components

Indexed keywords

BAYESIAN NETWORKS; INFERENCE ENGINES; NORMAL DISTRIBUTION; RANDOM PROCESSES; SAMPLING;

DIRICHLET PROCESS; DIRICHLET PROCESS PRIOR; IDENTIFIABILITY; MIXED MODELING; POSTPROCESSING; RANDOM EFFECTS; SEMIPARAMETRIC; SMOOTHING SPLINE; UNIFORM SHRINKAGE PRIOR; VARIANCE COMPONENTS;

SHRINKAGE;

BAYESIAN ANALYSIS; DATA SET; HORMONE; IDENTIFICATION METHOD; MODEL TEST; PARAMETERIZATION; REGRESSION ANALYSIS; SAMPLE PREPARATION; SHRINKAGE; SMOOTHING; VARIANCE ANALYSIS;

ALGORITHM; BAYES THEOREM; BIOMETRY; COMPUTER SIMULATION; EPIDEMIOLOGY; INFORMATION RETRIEVAL; LONGITUDINAL STUDY; PROCEDURES; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; BAYES THEOREM; BIOMETRY; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; EPIDEMIOLOGIC METHODS; INFORMATION STORAGE AND RETRIEVAL; LONGITUDINAL STUDIES; MODELS, STATISTICAL;

EID: 77949678206     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2009.01227.x     Document Type: Article

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