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A Bayesian approach to estimating variance components within a multivariate generalizability theory framework

Overview of attention for article published in Behavior Research Methods, December 2017
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2 X users

Citations

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17 Mendeley
Title
A Bayesian approach to estimating variance components within a multivariate generalizability theory framework
Published in
Behavior Research Methods, December 2017
DOI 10.3758/s13428-017-0986-3
Pubmed ID
Authors

Zhehan Jiang, William Skorupski

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 29%
Student > Ph. D. Student 4 24%
Student > Doctoral Student 3 18%
Professor 1 6%
Student > Master 1 6%
Other 1 6%
Unknown 2 12%
Readers by discipline Count As %
Psychology 5 29%
Social Sciences 4 24%
Medicine and Dentistry 3 18%
Linguistics 1 6%
Immunology and Microbiology 1 6%
Other 0 0%
Unknown 3 18%
Attention Score in Context

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 09 April 2024.
All research outputs
#20,183,117
of 25,670,640 outputs
Outputs from Behavior Research Methods
#1,892
of 2,565 outputs
Outputs of similar age
#322,259
of 445,652 outputs
Outputs of similar age from Behavior Research Methods
#22
of 31 outputs
Altmetric has tracked 25,670,640 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,565 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 22nd percentile – i.e., 22% 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 445,652 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.