| Title |
Multiple imputation methods for handling missing values in a longitudinal categorical variable with restrictions on transitions over time: a simulation study
|
|---|---|
| Published in |
BMC Medical Research Methodology, January 2019
|
| DOI | 10.1186/s12874-018-0653-0 |
| Pubmed ID | |
| Authors |
Anurika Priyanjali De Silva, Margarita Moreno-Betancur, Alysha Madhu De Livera, Katherine Jane Lee, Julie Anne Simpson |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 22% |
| Australia | 2 | 22% |
| South Africa | 1 | 11% |
| United Kingdom | 1 | 11% |
| Unknown | 3 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 56% |
| Scientists | 4 | 44% |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 72 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 14% |
| Student > Ph. D. Student | 8 | 11% |
| Student > Bachelor | 7 | 10% |
| Student > Doctoral Student | 6 | 8% |
| Researcher | 5 | 7% |
| Other | 12 | 17% |
| Unknown | 24 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Mathematics | 10 | 14% |
| Medicine and Dentistry | 6 | 8% |
| Nursing and Health Professions | 5 | 7% |
| Social Sciences | 5 | 7% |
| Arts and Humanities | 4 | 6% |
| Other | 14 | 19% |
| Unknown | 28 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 February 2020.
All research outputs
#2,735,551
of 25,287,709 outputs
Outputs from BMC Medical Research Methodology
#410
of 2,257 outputs
Outputs of similar age
#60,903
of 450,561 outputs
Outputs of similar age from BMC Medical Research Methodology
#19
of 58 outputs
Altmetric has tracked 25,287,709 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,257 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one has done well, scoring higher than 81% 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 450,561 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 86% of its contemporaries.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.