Variable selection and structural discovery in joint models of longitudinal and survival data

Variable selection and structural discovery in joint models of longitudinal and survival data

Indiana University-Purdue University Indianapolis (IUPUI) === Joint models of longitudinal and survival outcomes have been used with increasing frequency in clinical investigations. Correct specification of fixed and random effects, as well as their functional forms is essential for practical data a...

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Bibliographic Details
Main Author: He, Zangdong
Other Authors: Tu, Wanzhu
Language:en_US
Published: 2015
Subjects:
Joint models
Mixed effect selection
Structural discovery
Adaptive LASSO
Gaussian quadrature
EM algorithm
Gaussian quadrature formulas > Research > Analysis
Linear models (Statistics) > Research > Analysis
Expectation-maximization algorithms > Research
Regression analysis > Data processing
Numerical analysis > Data processing
Survival analysis (Biometry) > Data processing
Spectral theory (Mathematics)
Mathematical statistics > Longitudinal studies
Estimation theory > Analysis
Statistics > Data processing
Calculus of variations
Structural bioinformatics
Parameter estimation
Online Access:http://hdl.handle.net/1805/6365

Internet

http://hdl.handle.net/1805/6365

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