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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using informative prior based on expert opinion in Bayesian estimation of the transition probability matrix in Markov modelling—an example from the cost-effectiveness analysis of the treatment of patients with predominantly negative symptoms of schizophrenia with cariprazine
|
|---|---|
| Published in |
Cost Effectiveness and Resource Allocation, August 2020
|
| DOI | 10.1186/s12962-020-00224-w |
| Pubmed ID | |
| Authors |
Zoltán Vokó, István Bitter, Beatrix Mersich, János Réthelyi, Anett Molnár, János G. Pitter, Árpád Götze, Margit Horváth, Kristóf Kóczián, Laura Fonticoli, Filippo Lelli, Bertalan Németh |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 21% |
| Student > Bachelor | 2 | 11% |
| Student > Ph. D. Student | 2 | 11% |
| Other | 1 | 5% |
| Student > Doctoral Student | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 7 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 3 | 16% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 11% |
| Nursing and Health Professions | 2 | 11% |
| Business, Management and Accounting | 1 | 5% |
| Mathematics | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 9 | 47% |
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 28 August 2020.
All research outputs
#18,078,691
of 23,232,430 outputs
Outputs from Cost Effectiveness and Resource Allocation
#341
of 433 outputs
Outputs of similar age
#284,781
of 399,131 outputs
Outputs of similar age from Cost Effectiveness and Resource Allocation
#11
of 20 outputs
Altmetric has tracked 23,232,430 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 433 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one is in the 17th percentile – i.e., 17% 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 399,131 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 20 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.