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Joint modelling of time-to-event and multivariate longitudinal outcomes: recent developments and issues

Overview of attention for article published in BMC Medical Research Methodology, September 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)

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5 tweeters
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1 patent

Citations

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56 Dimensions

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163 Mendeley
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Title
Joint modelling of time-to-event and multivariate longitudinal outcomes: recent developments and issues
Published in
BMC Medical Research Methodology, September 2016
DOI 10.1186/s12874-016-0212-5
Pubmed ID
Authors

Graeme L. Hickey, Pete Philipson, Andrea Jorgensen, Ruwanthi Kolamunnage-Dona

Abstract

Available methods for the joint modelling of longitudinal and time-to-event outcomes have typically only allowed for a single longitudinal outcome and a solitary event time. In practice, clinical studies are likely to record multiple longitudinal outcomes. Incorporating all sources of data will improve the predictive capability of any model and lead to more informative inferences for the purpose of medical decision-making. We reviewed current methodologies of joint modelling for time-to-event data and multivariate longitudinal data including the distributional and modelling assumptions, the association structures, estimation approaches, software tools for implementation and clinical applications of the methodologies. We found that a large number of different models have recently been proposed. Most considered jointly modelling linear mixed models with proportional hazard models, with correlation between multiple longitudinal outcomes accounted for through multivariate normally distributed random effects. So-called current value and random effects parameterisations are commonly used to link the models. Despite developments, software is still lacking, which has translated into limited uptake by medical researchers. Although, in an era of personalized medicine, the value of multivariate joint modelling has been established, researchers are currently limited in their ability to fit these models routinely. We make a series of recommendations for future research needs.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 162 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 43 26%
Student > Ph. D. Student 36 22%
Student > Master 16 10%
Student > Doctoral Student 10 6%
Professor 5 3%
Other 25 15%
Unknown 28 17%
Readers by discipline Count As %
Mathematics 45 28%
Medicine and Dentistry 24 15%
Engineering 8 5%
Agricultural and Biological Sciences 6 4%
Computer Science 6 4%
Other 33 20%
Unknown 41 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 September 2018.
All research outputs
#3,328,136
of 16,849,755 outputs
Outputs from BMC Medical Research Methodology
#561
of 1,576 outputs
Outputs of similar age
#65,862
of 269,250 outputs
Outputs of similar age from BMC Medical Research Methodology
#1
of 1 outputs
Altmetric has tracked 16,849,755 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,576 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one has gotten more attention than average, scoring higher than 64% of its peers.
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We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them