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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A new visualization and conceptualization of categorical longitudinal development: measurement invariance and change
|
|---|---|
| Published in |
Frontiers in Psychology, March 2015
|
| DOI | 10.3389/fpsyg.2015.00289 |
| Pubmed ID | |
| Authors |
Jan Boom |
| Abstract |
The Overlapping Waves Model (OWM) is a metaphor introduced by Siegler (1996) to illustrate a typical sequence of increasing and decreasing use of strategies during development. Going beyond metaphor, a new model synthesized from Latent Growth Modeling (LGM) and Item Response Theory (IRT) will be presented to analyze such categorical longitudinal data. Use of strategies can be scored as a variable with only a few ordinal categories. IRT provides the means to relate the usage of strategies to position on an underlying developmental dimension. LGM allows to model movement of individuals along this dimension, acknowledging individual differences both in starting point and in speed of progress. Measuring and modeling such strategy development requires that at each time point the same categories are used, in the sense that item difficulties must remain invariant over time. Whether, discrimination can be relaxed is still an issue. The problem that had to be solved was disentangling the between-person-individual differences from real intra-individual developmental differences. Figures with polytomous or multi-category Item Characteristic Curves (ICC's) resemble the OWM in many respects. However, such figures are usually taken to represent inter-individual differences, whereas the OWM usually represents development (so intra-individual differences), and we cannot have both at the same time. The solution came from creating a framework with ability differences on one axis and the effect of time on another axis, resulting in a 3-D model. These (orthogonal) dimensions make it possible to adequately conceptualize measurement invariance in this complex context. As the result is difficult to conceptualize without extensive visualization, special 3-D figures will be used to illustrate and a dynamic (rotatable and scalable) version will be made available as Computable Document Format object (Mathematica). The model was successfully applied in several microgenetic studies. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 4% |
| Unknown | 26 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 30% |
| Student > Doctoral Student | 5 | 19% |
| Researcher | 4 | 15% |
| Student > Bachelor | 4 | 15% |
| Professor > Associate Professor | 2 | 7% |
| Other | 3 | 11% |
| Unknown | 1 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 13 | 48% |
| Medicine and Dentistry | 4 | 15% |
| Social Sciences | 3 | 11% |
| Computer Science | 2 | 7% |
| Mathematics | 2 | 7% |
| Other | 3 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 March 2015.
All research outputs
#14,806,069
of 22,797,621 outputs
Outputs from Frontiers in Psychology
#16,073
of 29,708 outputs
Outputs of similar age
#148,348
of 263,549 outputs
Outputs of similar age from Frontiers in Psychology
#337
of 471 outputs
Altmetric has tracked 22,797,621 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 29,708 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 38th percentile – i.e., 38% 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 263,549 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 471 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.