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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

  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

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8 X users

Citations

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273 Dimensions

Readers on

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999 Mendeley
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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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 999 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 10 1%
United Kingdom 4 <1%
Spain 3 <1%
Portugal 2 <1%
United States 2 <1%
Brazil 2 <1%
Canada 2 <1%
France 1 <1%
Sweden 1 <1%
Other 6 <1%
Unknown 966 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 372 37%
Student > Master 102 10%
Student > Doctoral Student 82 8%
Lecturer 65 7%
Researcher 53 5%
Other 180 18%
Unknown 145 15%
Readers by discipline Count As %
Business, Management and Accounting 309 31%
Social Sciences 169 17%
Psychology 100 10%
Computer Science 49 5%
Economics, Econometrics and Finance 41 4%
Other 127 13%
Unknown 204 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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
#6,448,853
of 23,881,329 outputs
Outputs from BMC Medical Research Methodology
#966
of 2,109 outputs
Outputs of similar age
#46,629
of 184,178 outputs
Outputs of similar age from BMC Medical Research Methodology
#8
of 29 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 2,109 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 54% 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 184,178 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.