Identification of risk factors for hospital admission using multiple-failure survival models: a toolkit for researchers

about

Identification of risk factors for hospital admission using multiple-failure survival models: a toolkit for researchers

Item

http://www.wikidata.org/entity/Q35999924

description

2016 nî lūn-bûn

@nan

2016年の論文

@ja

2016年論文

@yue

2016年論文

@zh-hant

2016年論文

@zh-hk

2016年論文

@zh-mo

2016年論文

@zh-tw

2016年论文

@wuu

2016年论文

@zh

2016年论文

@zh-cn

name

Identification of risk factors ...... els: a toolkit for researchers

@ast

Identification of risk factors ...... els: a toolkit for researchers

@en

type

Item

label

Identification of risk factors ...... els: a toolkit for researchers

@ast

Identification of risk factors ...... els: a toolkit for researchers

@en

prefLabel

Identification of risk factors ...... els: a toolkit for researchers

@ast

Identification of risk factors ...... els: a toolkit for researchers

@en

P1476

Identification of risk factors ...... els: a toolkit for researchers

@en

P2093

Holly E Syddall

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

Leo D Westbury

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

Shirley J Simmonds

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

P2860

Cohort Profile: The 1946 National Birth Cohort (MRC National Survey of Health and Development)

Predicting risk of emergency admission to hospital using primary care data: derivation and validation of QAdmissions score.

Multi-state models for the analysis of time-to-event data.

Repeated occurrence of basal cell carcinoma of the skin and multifailure survival analysis: follow-up data from the Nambour Skin Cancer Prevention Trial.

Understanding NHS hospital admissions in England: linkage of Hospital Episode Statistics to the Hertfordshire Cohort Study.

Cohort profile: the Hertfordshire cohort study.

Treatment of death in the analysis of longitudinal studies of gerontological outcomes

Empirical study of correlated survival times for recurrent events with proportional hazards margins and the effect of correlation and censoring.

Case finding for patients at risk of readmission to hospital: development of algorithm to identify high risk patients.

The use and interpretation of competing risks regression models

P2888

s12874-016-0147-x

P304

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

P31

scholarly article

P356

10.1186/S12874-016-0147-X

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

P478

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

P50

Avan Aihie Sayer

Cyrus Cooper

P577

2016-04-26T00:00:00Z

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

P6179

1051567424

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

P698

27117081

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

P932

4845493

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