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Testing the proportional hazards assumption in case-cohort analysis

Overview of attention for article published in BMC Medical Research Methodology, July 2013
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)

Mentioned by

twitter
5 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
58 Dimensions

Readers on

mendeley
77 Mendeley
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Title
Testing the proportional hazards assumption in case-cohort analysis
Published in
BMC Medical Research Methodology, July 2013
DOI 10.1186/1471-2288-13-88
Pubmed ID
Authors

Xiaonan Xue, Xianhong Xie, Marc Gunter, Thomas E Rohan, Sylvia Wassertheil-Smoller, Gloria YF Ho, Dominic Cirillo, Herbert Yu, Howard D Strickler

Abstract

Case-cohort studies have become common in epidemiological studies of rare disease, with Cox regression models the principal method used in their analysis. However, no appropriate procedures to assess the assumption of proportional hazards of case-cohort Cox models have been proposed.

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 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
Unknown 76 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 27%
Student > Master 14 18%
Researcher 10 13%
Other 5 6%
Student > Bachelor 5 6%
Other 10 13%
Unknown 12 16%
Readers by discipline Count As %
Medicine and Dentistry 22 29%
Agricultural and Biological Sciences 6 8%
Biochemistry, Genetics and Molecular Biology 3 4%
Business, Management and Accounting 3 4%
Environmental Science 3 4%
Other 22 29%
Unknown 18 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 02 June 2021.
All research outputs
#10,188,204
of 18,783,186 outputs
Outputs from BMC Medical Research Methodology
#999
of 1,702 outputs
Outputs of similar age
#76,359
of 168,135 outputs
Outputs of similar age from BMC Medical Research Methodology
#1
of 1 outputs
Altmetric has tracked 18,783,186 research outputs across all sources so far. This one is in the 45th percentile – i.e., 45% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,702 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 168,135 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
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