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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The Differential Time-Varying Effect Model (DTVEM): A tool for diagnosing and modeling time lags in intensive longitudinal data
|
|---|---|
| Published in |
Behavior Research Methods, August 2018
|
| DOI | 10.3758/s13428-018-1101-0 |
| Pubmed ID | |
| Authors |
Nicholas C. Jacobson, Sy-Miin Chow, Michelle G. Newman |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 33% |
| Netherlands | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 17% |
| Members of the public | 1 | 17% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 82 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 21% |
| Student > Doctoral Student | 10 | 12% |
| Researcher | 9 | 11% |
| Student > Postgraduate | 6 | 7% |
| Student > Bachelor | 4 | 5% |
| Other | 15 | 18% |
| Unknown | 21 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 28 | 34% |
| Social Sciences | 11 | 13% |
| Medicine and Dentistry | 3 | 4% |
| Nursing and Health Professions | 2 | 2% |
| Agricultural and Biological Sciences | 2 | 2% |
| Other | 7 | 9% |
| Unknown | 29 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 04 May 2023.
All research outputs
#7,901,007
of 25,385,509 outputs
Outputs from Behavior Research Methods
#966
of 2,526 outputs
Outputs of similar age
#126,173
of 341,403 outputs
Outputs of similar age from Behavior Research Methods
#31
of 48 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 68th 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 61% 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 341,403 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 62% of its contemporaries.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.