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Designing cost-efficient randomized trials by using flexible recruitment strategies

Overview of attention for article published in BMC Medical Research Methodology, July 2012
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Mentioned by

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1 tweeter

Citations

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1 Dimensions

Readers on

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10 Mendeley
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1 CiteULike
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Title
Designing cost-efficient randomized trials by using flexible recruitment strategies
Published in
BMC Medical Research Methodology, July 2012
DOI 10.1186/1471-2288-12-106
Pubmed ID
Authors

Menggang Yu, Jingwei Wu, Debra S Burns, Janet S Carpenter

Abstract

Sample size planning for clinical trials is usually based on detecting a target effect size of an intervention or treatment. Explicit incorporation of costs into such planning is considered in this article in the situation where effects of an intervention or treatment may depend on (interact with) baseline severity of the targeted symptom or disease. Because much larger sample sizes are usually required to establish such an interaction effect, investigators frequently conduct studies to establish a marginal effect of the intervention for individuals with a certain level of baseline severity.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 10%
Unknown 9 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 40%
Other 2 20%
Student > Master 1 10%
Student > Doctoral Student 1 10%
Researcher 1 10%
Other 1 10%
Readers by discipline Count As %
Medicine and Dentistry 6 60%
Computer Science 1 10%
Pharmacology, Toxicology and Pharmaceutical Science 1 10%
Earth and Planetary Sciences 1 10%
Philosophy 1 10%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 24 November 2012.
All research outputs
#7,762,387
of 12,373,180 outputs
Outputs from BMC Medical Research Methodology
#778
of 1,095 outputs
Outputs of similar age
#141,088
of 258,863 outputs
Outputs of similar age from BMC Medical Research Methodology
#55
of 98 outputs
Altmetric has tracked 12,373,180 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,095 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one is in the 20th percentile – i.e., 20% 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 258,863 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 98 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.