Hidden Markov models as a tool for sequential eye movement analysis: A replication

Stuijfzand, B.G. and Browne, W.J. and Baddeley, R.J. (2018). Hidden Markov models as a tool for sequential eye movement analysis: A replication. [Data Collection]. Colchester, Essex: UK Data Archive. 10.5255/UKDA-SN-853080

Data description (abstract)

This dataset contains the eye movement data of 19 participants engaged in an information search experiment involving two tasks. In each task, the participant was presented with a set of 10 news headlines (in English) and the participant was instructed to either: find a pre-specified word in the headlines (task 1), or, select the headline which they found most interesting (task 2). Each task occurred 50 times (the tasks occurred in a randomised sequence), with the experiment therefore totalling 100 trials, on 50 unique sets of headlines (the headlines were repeated for each task). The dataset contains 84566 rows. Each row in the dataset contains a single fixation-saccade sequence (i.e. “event”), with information on event timestamps, fixation and saccade location coordinates, saccade velocity, and saccade amplitude available. Further, for each row there are numerical identifiers for the trial, experimental block, type of task, set of news headlines used, and participant (anonymised) available. An additional demographic dataset is avaible containing the age and sex of the participants. This dataset was collected for chapter 4 in the following work: Stuijfzand, B. G. (2016). Advanced statistical methods to interpret eye movements : on time-series and individual differences (PhD thesis). See Related Resources.

Data creators:
Creator Name Affiliation ORCID (as URL)
Stuijfzand B.G. University of Bristol https://orcid.org/0000-0002-2782-3408
Browne W.J. University of Bristol
Baddeley R.J. University of Bristol
Sponsors: Economic and Social Research Council
Grant reference: ES/J50015X/1
Topic classification: Psychology
Keywords: eye movements, visual search
Project title: Addressing methodological limitations of eye tracking research: Using a Bayesian framework for advanced analysis of gazepatterns
Grant holders: Bobby Stuijfzand
Project dates:
FromTo
23 September 201325 September 2016
Date published: 13 Feb 2018 13:10
Last modified: 13 Feb 2018 13:11

Available Files

Data

Documentation

Read me

Downloads

data downloads and page views since this item was published

View more statistics

Altmetric

Edit item (login required)

Edit Item Edit Item