↓ Skip to main content

Adjusting for multiple prognostic factors in the analysis of randomised trials

Overview of attention for article published in BMC Medical Research Methodology, July 2013
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
51 Mendeley
citeulike
2 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Adjusting for multiple prognostic factors in the analysis of randomised trials
Published in
BMC Medical Research Methodology, July 2013
DOI 10.1186/1471-2288-13-99
Pubmed ID
Authors

Brennan C Kahan, Tim P Morris

Abstract

When multiple prognostic factors are adjusted for in the analysis of a randomised trial, it is unclear (1) whether it is necessary to account for each of the strata, formed by all combinations of the prognostic factors (stratified analysis), when randomisation has been balanced within each stratum (stratified randomisation), or whether adjusting for the main effects alone will suffice, and (2) the best method of adjustment in terms of type I error rate and power, irrespective of the randomisation method.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Germany 1 2%
Unknown 49 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 29%
Student > Master 8 16%
Student > Ph. D. Student 7 14%
Other 5 10%
Professor 3 6%
Other 8 16%
Unknown 5 10%
Readers by discipline Count As %
Medicine and Dentistry 16 31%
Mathematics 13 25%
Computer Science 2 4%
Nursing and Health Professions 2 4%
Social Sciences 2 4%
Other 6 12%
Unknown 10 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 May 2019.
All research outputs
#8,594,743
of 14,976,421 outputs
Outputs from BMC Medical Research Methodology
#890
of 1,386 outputs
Outputs of similar age
#75,078
of 158,061 outputs
Outputs of similar age from BMC Medical Research Methodology
#1
of 1 outputs
Altmetric has tracked 14,976,421 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,386 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one is in the 34th percentile – i.e., 34% 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 158,061 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 51% 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