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Should researchers use single indicators, best indicators, or multiple indicators in structural equation models?

Overview of attention for article published in BMC Medical Research Methodology, October 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

twitter
9 tweeters

Citations

dimensions_citation
129 Dimensions

Readers on

mendeley
617 Mendeley
Title
Should researchers use single indicators, best indicators, or multiple indicators in structural equation models?
Published in
BMC Medical Research Methodology, October 2012
DOI 10.1186/1471-2288-12-159
Pubmed ID
Authors

Leslie A Hayduk, Levente Littvay

Abstract

Structural equation modeling developed as a statistical melding of path analysis and factor analysis that obscured a fundamental tension between a factor preference for multiple indicators and path modeling's openness to fewer indicators.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 617 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 10 2%
United Kingdom 4 <1%
United States 4 <1%
Portugal 3 <1%
Spain 3 <1%
Canada 2 <1%
Brazil 2 <1%
France 1 <1%
Switzerland 1 <1%
Other 6 <1%
Unknown 581 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 282 46%
Student > Master 64 10%
Student > Doctoral Student 60 10%
Lecturer 34 6%
Researcher 34 6%
Other 111 18%
Unknown 32 5%
Readers by discipline Count As %
Business, Management and Accounting 210 34%
Social Sciences 129 21%
Psychology 73 12%
Computer Science 36 6%
Economics, Econometrics and Finance 20 3%
Other 77 12%
Unknown 72 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 08 June 2017.
All research outputs
#2,130,235
of 12,373,180 outputs
Outputs from BMC Medical Research Methodology
#329
of 1,095 outputs
Outputs of similar age
#23,227
of 137,984 outputs
Outputs of similar age from BMC Medical Research Methodology
#16
of 115 outputs
Altmetric has tracked 12,373,180 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,095 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one has gotten more attention than average, scoring higher than 69% 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 137,984 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 83% of its contemporaries.
We're also able to compare this research output to 115 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.