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X Demographics
Mendeley readers
Attention Score in Context
| Title |
What’s more general than a whole population?
|
|---|---|
| Published in |
Emerging Themes in Epidemiology, August 2015
|
| DOI | 10.1186/s12982-015-0029-4 |
| Pubmed ID | |
| Authors |
Neal Alexander |
| Abstract |
Statistical inference is commonly said to be inapplicable to complete population studies, such as censuses, due to the absence of sampling variability. Nevertheless, in recent years, studies of whole populations, e.g., all cases of a certain cancer in a given country, have become more common, and often report p values and confidence intervals regardless of such concerns. With reference to the social science literature, the current paper explores the circumstances under which statistical inference can be meaningful for such studies. It concludes that its use implicitly requires a target population which is wider than the whole population studied - for example future cases, or a supranational geographic region - and that the validity of such statistical analysis depends on the generalizability of the whole to the target population. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Saudi Arabia | 4 | 57% |
| Unknown | 3 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 52 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 21% |
| Student > Ph. D. Student | 10 | 19% |
| Student > Master | 9 | 17% |
| Professor | 4 | 8% |
| Other | 3 | 6% |
| Other | 9 | 17% |
| Unknown | 6 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 18 | 35% |
| Social Sciences | 9 | 17% |
| Nursing and Health Professions | 2 | 4% |
| Business, Management and Accounting | 2 | 4% |
| Mathematics | 2 | 4% |
| Other | 10 | 19% |
| Unknown | 9 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 28 December 2020.
All research outputs
#6,038,908
of 24,635,922 outputs
Outputs from Emerging Themes in Epidemiology
#56
of 152 outputs
Outputs of similar age
#66,333
of 272,822 outputs
Outputs of similar age from Emerging Themes in Epidemiology
#3
of 4 outputs
Altmetric has tracked 24,635,922 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 152 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one has gotten more attention than average, scoring higher than 63% of its peers.
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 272,822 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.