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

DOI

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.

This method description is an edited extract from 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). See ExperimentProtocol document.

Identifier
DOI https://doi.org/10.5255/UKDA-SN-853080
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=7d48405ac5876bf33fb9f0ca70e146ce560af290934d11b1ec4ffe90e5fe4788
Provenance
Creator Stuijfzand, B, University of Bristol; Browne, W, University of Bristol; Baddeley, R, University of Bristol
Publisher UK Data Service
Publication Year 2018
Funding Reference Economic and Social Research Council
Rights B.G. Stuijfzand, University of Bristol; The Data Collection is available to any user without the requirement for registration for download/access.
OpenAccess true
Representation
Resource Type Numeric
Discipline Psychology; Social and Behavioural Sciences
Spatial Coverage Bristol; United Kingdom