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Attention Score in Context
| Title |
An empirical comparison of methods for analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening
|
|---|---|
| Published in |
BMC Medical Research Methodology, February 2012
|
| DOI | 10.1186/1471-2288-12-15 |
| Pubmed ID | |
| Authors |
Ji Cheng, Eleanor Pullenayegum, Deborah A Marshall, John K Marshall, Lehana Thabane |
| Abstract |
A discrete choice experiment (DCE) is a preference survey which asks participants to make a choice among product portfolios comparing the key product characteristics by performing several choice tasks. Analyzing DCE data needs to account for within-participant correlation because choices from the same participant are likely to be similar. In this study, we empirically compared some commonly-used statistical methods for analyzing DCE data while accounting for within-participant correlation based on a survey of patient preference for colorectal cancer (CRC) screening tests conducted in Hamilton, Ontario, Canada in 2002. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 2 | 3% |
| Kenya | 1 | 2% |
| Switzerland | 1 | 2% |
| Unknown | 54 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 21% |
| Student > Ph. D. Student | 9 | 16% |
| Student > Master | 7 | 12% |
| Student > Doctoral Student | 6 | 10% |
| Other | 5 | 9% |
| Other | 8 | 14% |
| Unknown | 11 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 19% |
| Economics, Econometrics and Finance | 7 | 12% |
| Agricultural and Biological Sciences | 5 | 9% |
| Business, Management and Accounting | 5 | 9% |
| Psychology | 3 | 5% |
| Other | 15 | 26% |
| Unknown | 12 | 21% |
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 12 March 2012.
All research outputs
#15,242,272
of 22,663,150 outputs
Outputs from BMC Medical Research Methodology
#1,499
of 2,000 outputs
Outputs of similar age
#100,493
of 156,574 outputs
Outputs of similar age from BMC Medical Research Methodology
#18
of 32 outputs
Altmetric has tracked 22,663,150 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,000 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 16th percentile – i.e., 16% 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 156,574 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.