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Model fit evaluation in multilevel structural equation models

Overview of attention for article published in Frontiers in Psychology, January 2014
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Title
Model fit evaluation in multilevel structural equation models
Published in
Frontiers in Psychology, January 2014
DOI 10.3389/fpsyg.2014.00081
Pubmed ID
Authors

Ehri Ryu

Abstract

Assessing goodness of model fit is one of the key questions in structural equation modeling (SEM). Goodness of fit is the extent to which the hypothesized model reproduces the multivariate structure underlying the set of variables. During the earlier development of multilevel structural equation models, the "standard" approach was to evaluate the goodness of fit for the entire model across all levels simultaneously. The model fit statistics produced by the standard approach have a potential problem in detecting lack of fit in the higher-level model for which the effective sample size is much smaller. Also when the standard approach results in poor model fit, it is not clear at which level the model does not fit well. This article reviews two alternative approaches that have been proposed to overcome the limitations of the standard approach. One is a two-step procedure which first produces estimates of saturated covariance matrices at each level and then performs single-level analysis at each level with the estimated covariance matrices as input (Yuan and Bentler, 2007). The other level-specific approach utilizes partially saturated models to obtain test statistics and fit indices for each level separately (Ryu and West, 2009). Simulation studies (e.g., Yuan and Bentler, 2007; Ryu and West, 2009) have consistently shown that both alternative approaches performed well in detecting lack of fit at any level, whereas the standard approach failed to detect lack of fit at the higher level. It is recommended that the alternative approaches are used to assess the model fit in multilevel structural equation model. Advantages and disadvantages of the two alternative approaches are discussed. The alternative approaches are demonstrated in an empirical example.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
United Kingdom 1 <1%
Chile 1 <1%
Singapore 1 <1%
Serbia 1 <1%
Unknown 154 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 26%
Researcher 20 13%
Student > Master 20 13%
Student > Doctoral Student 16 10%
Professor > Associate Professor 11 7%
Other 26 16%
Unknown 26 16%
Readers by discipline Count As %
Psychology 38 24%
Social Sciences 28 18%
Business, Management and Accounting 20 13%
Nursing and Health Professions 6 4%
Medicine and Dentistry 6 4%
Other 27 17%
Unknown 35 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 11 April 2016.
All research outputs
#13,707,147
of 22,743,667 outputs
Outputs from Frontiers in Psychology
#13,827
of 29,608 outputs
Outputs of similar age
#167,431
of 305,223 outputs
Outputs of similar age from Frontiers in Psychology
#116
of 182 outputs
Altmetric has tracked 22,743,667 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 29,608 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one has gotten more attention than average, scoring higher than 52% 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 305,223 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 182 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.