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Attention Score in Context
| Title |
A pairwise pseudo-likelihood approach for regression analysis of left-truncated failure time data with various types of censoring
|
|---|---|
| Published in |
BMC Medical Research Methodology, April 2023
|
| DOI | 10.1186/s12874-023-01903-x |
| Pubmed ID | |
| Authors |
Li Shao, Hongxi Li, Shuwei Li, Jianguo Sun |
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 06 May 2023.
All research outputs
#6,033,668
of 23,746,606 outputs
Outputs from BMC Medical Research Methodology
#850
of 2,099 outputs
Outputs of similar age
#89,129
of 367,821 outputs
Outputs of similar age from BMC Medical Research Methodology
#14
of 47 outputs
Altmetric has tracked 23,746,606 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 2,099 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 55% 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 367,821 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 47 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.