You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
The Impact of Partial Measurement Invariance on Testing Moderation for Single and Multi-Level Data
|
|---|---|
| Published in |
Frontiers in Psychology, May 2018
|
| DOI | 10.3389/fpsyg.2018.00740 |
| Pubmed ID | |
| Authors |
Yu-Yu Hsiao, Mark H. C. Lai |
| Abstract |
Moderation effect is a commonly used concept in the field of social and behavioral science. Several studies regarding the implication of moderation effects have been done; however, little is known about how partial measurement invariance influences the properties of tests for moderation effects when categorical moderators were used. Additionally, whether the impact is the same across single and multilevel data is still unknown. Hence, the purpose of the present study is twofold: (a) To investigate the performance of the moderation test in single-level studies when measurement invariance does not hold; (b) To examine whether unique features of multilevel data, such as intraclass correlation (ICC) and number of clusters, influence the effect of measurement non-invariance on the performance of tests for moderation. Simulation results indicated that falsely assuming measurement invariance lead to biased estimates, inflated Type I error rates, and more gain or more loss in power (depends on simulation conditions) for the test of moderation effects. Such patterns were more salient as sample size and the number of non-invariant items increase for both single- and multi-level data. With multilevel data, the cluster size seemed to have a larger impact than the number of clusters when falsely assuming measurement invariance in the moderation estimation. ICC was trivially related to the moderation estimates. Overall, when testing moderation effects with categorical moderators, employing a model that accounts for the measurement (non)invariance structure of the predictor and/or the outcome is recommended. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 39 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 38% |
| Researcher | 5 | 13% |
| Student > Doctoral Student | 5 | 13% |
| Professor > Associate Professor | 2 | 5% |
| Student > Master | 2 | 5% |
| Other | 2 | 5% |
| Unknown | 8 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 16 | 41% |
| Social Sciences | 8 | 21% |
| Business, Management and Accounting | 5 | 13% |
| Agricultural and Biological Sciences | 1 | 3% |
| Medicine and Dentistry | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 8 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 27 April 2018.
All research outputs
#20,483,282
of 23,045,021 outputs
Outputs from Frontiers in Psychology
#24,468
of 30,353 outputs
Outputs of similar age
#287,331
of 326,942 outputs
Outputs of similar age from Frontiers in Psychology
#636
of 659 outputs
Altmetric has tracked 23,045,021 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 30,353 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 326,942 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% 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 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.