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Parsing eye-tracking data of variable quality to provide accurate fixation duration estimates in infants and adults

Overview of attention for article published in Behavior Research Methods, September 2012
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1 X user
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Citations

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254 Mendeley
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2 CiteULike
Title
Parsing eye-tracking data of variable quality to provide accurate fixation duration estimates in infants and adults
Published in
Behavior Research Methods, September 2012
DOI 10.3758/s13428-012-0245-6
Pubmed ID
Authors

S. V. Wass, T. J. Smith, M. H. Johnson

Abstract

Researchers studying infants' spontaneous allocation of attention have traditionally relied on hand-coding infants' direction of gaze from videos; these techniques have low temporal and spatial resolution and are labor intensive. Eye-tracking technology potentially allows for much more precise measurement of how attention is allocated at the subsecond scale, but a number of technical and methodological issues have given rise to caution about the quality and reliability of high temporal resolution data obtained from infants. We present analyses suggesting that when standard dispersal-based fixation detection algorithms are used to parse eye-tracking data obtained from infants, the results appear to be heavily influenced by interindividual variations in data quality. We discuss the causes of these artifacts, including fragmentary fixations arising from flickery or unreliable contact with the eyetracker and variable degrees of imprecision in reported position of gaze. We also present new algorithms designed to cope with these problems by including a number of new post hoc verification checks to identify and eliminate fixations that may be artifactual. We assess the results of our algorithms by testing their reliability using a variety of methods and on several data sets. We contend that, with appropriate data analysis methods, fixation duration can be a reliable and stable measure in infants. We conclude by discussing ways in which studying fixation durations during unconstrained orienting may offer insights into the relationship between attention and learning in naturalistic settings.

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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 254 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
United Kingdom 4 2%
France 2 <1%
Germany 1 <1%
Spain 1 <1%
Singapore 1 <1%
Unknown 241 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 67 26%
Researcher 48 19%
Student > Master 25 10%
Student > Bachelor 18 7%
Student > Doctoral Student 17 7%
Other 45 18%
Unknown 34 13%
Readers by discipline Count As %
Psychology 121 48%
Computer Science 16 6%
Neuroscience 16 6%
Linguistics 9 4%
Engineering 9 4%
Other 28 11%
Unknown 55 22%
Attention Score in Context

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 05 September 2016.
All research outputs
#16,047,334
of 25,373,627 outputs
Outputs from Behavior Research Methods
#1,469
of 2,525 outputs
Outputs of similar age
#114,854
of 186,940 outputs
Outputs of similar age from Behavior Research Methods
#12
of 22 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,525 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one is in the 39th percentile – i.e., 39% 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 186,940 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.