Hierarchical models for semi-competing risks data with application to quality of end-of-life care for pancreatic cancer

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Hierarchical models for semi-competing risks data with application to quality of end-of-life care for pancreatic cancer

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2016 nî lūn-bûn

@nan

2016年の論文

@ja

2016年学术文章

@wuu

2016年学术文章

@zh-cn

2016年学术文章

@zh-hans

2016年学术文章

@zh-my

2016年学术文章

@zh-sg

2016年學術文章

@yue

2016年學術文章

@zh

2016年學術文章

@zh-hant

name

Hierarchical models for semi-c ...... ife care for pancreatic cancer

@ast

Hierarchical models for semi-c ...... ife care for pancreatic cancer

@en

type

Item

label

Hierarchical models for semi-c ...... ife care for pancreatic cancer

@ast

Hierarchical models for semi-c ...... ife care for pancreatic cancer

@en

prefLabel

Hierarchical models for semi-c ...... ife care for pancreatic cancer

@ast

Hierarchical models for semi-c ...... ife care for pancreatic cancer

@en

P1476

Hierarchical models for semi-c ...... ife care for pancreatic cancer

@en

P2093

Deborah Schrag

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Francesca Dominici

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Kyu Ha Lee

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Sebastien Haneuse

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P2860

Investigating hospital heterogeneity with a multi-state frailty model: application to nosocomial pneumonia disease in intensive care units

Reversible jump Markov chain Monte Carlo computation and Bayesian model determination

Systematic review of comorbidity indices for administrative data.

Bayesian gamma frailty models for survival data with semi-competing risks and treatment switching.

Bayesian approach for flexible modeling of semicompeting risks data

Bayesian Semi-parametric Analysis of Semi-competing Risks Data: Investigating Hospital Readmission after a Pancreatic Cancer Diagnosis.

Analysing multicentre competing risks data with a mixed proportional hazards model for the subdistribution.

On robustness of marginal regression coefficient estimates and hazard functions in multivariate survival analysis of family data when the frailty distribution is mis-specified.

Regression modeling of semicompeting risks data.

Competing risks analysis of correlated failure time data.

P304

1075-1095

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P31

scholarly article

P356

10.1080/01621459.2016.1164052

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P407

English

P433

515

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P478

111

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P577

2016-10-18T00:00:00Z

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P698

28303074

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P818

1502.00526

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P932

5347153

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