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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Relating Measurement Invariance, Cross-Level Invariance, and Multilevel Reliability
|
|---|---|
| Published in |
Frontiers in Psychology, October 2017
|
| DOI | 10.3389/fpsyg.2017.01640 |
| Pubmed ID | |
| Authors |
Suzanne Jak, Terrence D. Jorgensen |
| Abstract |
Data often have a nested, multilevel structure, for example when data are collected from children in classrooms. This kind of data complicate the evaluation of reliability and measurement invariance, because several properties can be evaluated at both the individual level and the cluster level, as well as across levels. For example, cross-level invariance implies equal factor loadings across levels, which is needed to give latent variables at the two levels a similar interpretation. Reliability at a specific level refers to the ratio of true score variance over total variance at that level. This paper aims to shine light on the relation between reliability, cross-level invariance, and strong factorial invariance across clusters in multilevel data. Specifically, we will illustrate how strong factorial invariance across clusters implies cross-level invariance and perfect reliability at the between level in multilevel factor models. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Chile | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 90 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 28 | 31% |
| Researcher | 17 | 19% |
| Student > Doctoral Student | 6 | 7% |
| Student > Master | 6 | 7% |
| Professor > Associate Professor | 5 | 6% |
| Other | 12 | 13% |
| Unknown | 16 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 42 | 47% |
| Social Sciences | 13 | 14% |
| Business, Management and Accounting | 7 | 8% |
| Nursing and Health Professions | 3 | 3% |
| Arts and Humanities | 2 | 2% |
| Other | 8 | 9% |
| Unknown | 15 | 17% |
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 31 January 2022.
All research outputs
#6,357,974
of 23,025,074 outputs
Outputs from Frontiers in Psychology
#9,197
of 30,283 outputs
Outputs of similar age
#103,649
of 324,398 outputs
Outputs of similar age from Frontiers in Psychology
#261
of 601 outputs
Altmetric has tracked 23,025,074 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 30,283 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 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 324,398 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 67% of its contemporaries.
We're also able to compare this research output to 601 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.