| Title |
Comparison of model- and design-based approaches to detect the treatment effect and covariate by treatment interactions in three-level models for multisite cluster-randomized trials
|
|---|---|
| Published in |
Behavior Research Methods, July 2018
|
| DOI | 10.3758/s13428-018-1080-1 |
| Pubmed ID | |
| Authors |
Burak Aydin, James Algina, Walter L. Leite |
| Abstract |
In this study, we evaluated the estimation of three important parameters for data collected in a multisite cluster-randomized trial (MS-CRT): the treatment effect, and the treatment by covariate interactions at Levels 1 and 2. The Level 1 and Level 2 interaction parameters are the coefficients for the products of the treatment indicator, with the covariate centered on its Level 2 expected value and with the Level 2 expected value centered on its Level 3 expected value, respectively. A comparison of a model-based approach to design-based approaches was performed using simulation studies. The results showed that both approaches produced similar treatment effect estimates and interaction estimates at Level 1, as well as similar Type I error rates and statistical power. However, the estimate of the Level 2 interaction coefficient for the product of the treatment indicator and an arithmetic mean of the Level 1 covariate was severely biased in most conditions. Therefore, applied researchers should be cautious when using arithmetic means to form a treatment by covariate interaction at Level 2 in MS-CRT data. |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor > Associate Professor | 3 | 18% |
| Student > Doctoral Student | 2 | 12% |
| Student > Ph. D. Student | 2 | 12% |
| Student > Master | 2 | 12% |
| Researcher | 2 | 12% |
| Other | 2 | 12% |
| Unknown | 4 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 4 | 24% |
| Biochemistry, Genetics and Molecular Biology | 1 | 6% |
| Mathematics | 1 | 6% |
| Psychology | 1 | 6% |
| Nursing and Health Professions | 1 | 6% |
| Other | 2 | 12% |
| Unknown | 7 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 July 2018.
All research outputs
#6,600,606
of 25,385,509 outputs
Outputs from Behavior Research Methods
#809
of 2,526 outputs
Outputs of similar age
#105,126
of 340,738 outputs
Outputs of similar age from Behavior Research Methods
#33
of 50 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 2,526 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has gotten more attention than average, scoring higher than 67% of its peers.
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We're also able to compare this research output to 50 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.