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Analyzing Complex Longitudinal Data in Educational Research: A Demonstration With Project English Language and Literacy Acquisition (ELLA) Data Using xxM

Overview of attention for article published in Frontiers in Psychology, June 2018
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Title
Analyzing Complex Longitudinal Data in Educational Research: A Demonstration With Project English Language and Literacy Acquisition (ELLA) Data Using xxM
Published in
Frontiers in Psychology, June 2018
DOI 10.3389/fpsyg.2018.00790
Pubmed ID
Authors

Oi-Man Kwok, Mark Hok-Chio Lai, Fuhui Tong, Rafael Lara-Alecio, Beverly Irby, Myeongsun Yoon, Yu-Chen Yeh

Abstract

When analyzing complex longitudinal data, especially data from different educational settings, researchers generally focus only on the mean part (i.e., the regression coefficients), ignoring the equally important random part (i.e., the random effect variances) of the model. By using Project English Language and Literacy Acquisition (ELLA) data, we demonstrated the importance of taking the complex data structure into account by carefully specifying the random part of the model, showing that not only can it affect the variance estimates, the standard errors, and the tests of significance of the regression coefficients, it also can offer different perspectives of the data, such as information related to the developmental process. We used xxM (Mehta, 2013), which can flexibly estimate different grade-level variances separately and the potential carryover effect from each grade factor to the later time measures. Implications of the findings and limitations of the study are discussed.

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The data shown below were collected from the profiles of 5 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 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 20%
Lecturer 3 15%
Student > Doctoral Student 3 15%
Student > Master 2 10%
Lecturer > Senior Lecturer 1 5%
Other 2 10%
Unknown 5 25%
Readers by discipline Count As %
Psychology 4 20%
Social Sciences 4 20%
Engineering 3 15%
Linguistics 1 5%
Mathematics 1 5%
Other 1 5%
Unknown 6 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 June 2018.
All research outputs
#13,518,432
of 23,047,237 outputs
Outputs from Frontiers in Psychology
#13,141
of 30,358 outputs
Outputs of similar age
#168,573
of 329,694 outputs
Outputs of similar age from Frontiers in Psychology
#393
of 659 outputs
Altmetric has tracked 23,047,237 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 30,358 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 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 329,694 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 659 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.