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Sequential sampling model for multiattribute choice alternatives with random attention time and processing order

Overview of attention for article published in Frontiers in Human Neuroscience, September 2014
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Title
Sequential sampling model for multiattribute choice alternatives with random attention time and processing order
Published in
Frontiers in Human Neuroscience, September 2014
DOI 10.3389/fnhum.2014.00697
Pubmed ID
Authors

Adele Diederich, Peter Oswald

Abstract

A sequential sampling model for multiattribute binary choice options, called multiattribute attention switching (MAAS) model, assumes a separate sampling process for each attribute. During the deliberation process attention switches from one attribute consideration to the next. The order in which attributes are considered as well for how long each attribute is considered-the attention time-influences the predicted choice probabilities and choice response times. Several probability distributions for the attention time with different variances are investigated. Depending on the time and order schedule the model predicts a rich choice probability/choice response time pattern including preference reversals and fast errors. Furthermore, the difference between finite and infinite decision horizons for the attribute considered last is investigated. For the former case the model predicts a probability p 0 > 0 of not deciding within the available time. The underlying stochastic process for each attribute is an Ornstein-Uhlenbeck process approximated by a discrete birth-death process. All predictions are also true for the widely applied Wiener process.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 43 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 23%
Researcher 8 18%
Student > Bachelor 5 11%
Professor 5 11%
Student > Doctoral Student 2 5%
Other 8 18%
Unknown 6 14%
Readers by discipline Count As %
Psychology 15 34%
Neuroscience 8 18%
Physics and Astronomy 3 7%
Agricultural and Biological Sciences 2 5%
Computer Science 2 5%
Other 5 11%
Unknown 9 20%
Attention Score in Context

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 10 September 2014.
All research outputs
#18,378,085
of 22,763,032 outputs
Outputs from Frontiers in Human Neuroscience
#6,058
of 7,139 outputs
Outputs of similar age
#170,229
of 238,632 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#219
of 259 outputs
Altmetric has tracked 22,763,032 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,139 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one is in the 8th percentile – i.e., 8% 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 238,632 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 259 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.