DYNAMIC PREDICTION FOR MULTIPLE REPEATED MEASURES AND EVENT TIME DATA: AN APPLICATION TO PARKINSON'S DISEASE.

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DYNAMIC PREDICTION FOR MULTIPLE REPEATED MEASURES AND EVENT TIME DATA: AN APPLICATION TO PARKINSON'S DISEASE.

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http://www.wikidata.org/entity/Q42976854

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2017 nî lūn-bûn

@nan

2017年の論文

@ja

2017年論文

@yue

2017年論文

@zh-hant

2017年論文

@zh-hk

2017年論文

@zh-mo

2017年論文

@zh-tw

2017年论文

@wuu

2017年论文

@zh

2017年论文

@zh-cn

name

DYNAMIC PREDICTION FOR MULTIPL ...... CATION TO PARKINSON'S DISEASE.

@en

DYNAMIC PREDICTION FOR MULTIPL ...... CATION TO PARKINSON'S DISEASE.

@nl

type

Item

label

DYNAMIC PREDICTION FOR MULTIPL ...... CATION TO PARKINSON'S DISEASE.

@en

DYNAMIC PREDICTION FOR MULTIPL ...... CATION TO PARKINSON'S DISEASE.

@nl

prefLabel

DYNAMIC PREDICTION FOR MULTIPL ...... CATION TO PARKINSON'S DISEASE.

@en

DYNAMIC PREDICTION FOR MULTIPL ...... CATION TO PARKINSON'S DISEASE.

@nl

P1476

DYNAMIC PREDICTION FOR MULTIPL ...... CATION TO PARKINSON'S DISEASE.

@en

P2093

Jue Wang

http://www.w3.org/2001/XMLSchema#string

Liang Li

http://www.w3.org/2001/XMLSchema#string

Sheng Luo

http://www.w3.org/2001/XMLSchema#string

P2860

Analysis of multivariate mixed longitudinal data: a flexible latent process approach.

Joint modeling of multivariate longitudinal measurements and survival data with applications to Parkinson's disease

A copula-based model for multivariate non-normal longitudinal data: analysis of a dose titration safety study on a new antidepressant.

Joint modelling of longitudinal measurements and event time data.

Bayesian hierarchical model for multiple repeated measures and survival data: an application to Parkinson's disease

Multilevel IRT using dichotomous and polytomous response data.

Shared parameter models for the joint analysis of longitudinal data and event times.

Joint models for multivariate longitudinal and multivariate survival data.

An approach to joint analysis of longitudinal measurements and competing risks failure time data.

Bayesian methods for latent trait modelling of longitudinal data.

P304

1787-1809

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P31

scholarly article

P356

10.1214/17-AOAS1059

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P433

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P478

http://www.w3.org/2001/XMLSchema#string

P577

2017-09-01T00:00:00Z

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P698

29081873

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P818

1603.06476

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5656296

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