May 4, 2022 Dataset Open Access

Bruns, Patrick

JSON Export

{"conceptdoi":"10.25592/uhhfdm.10182","conceptrecid":"10182","created":"2022-05-04T12:01:56.791453+00:00","doi":"10.25592/uhhfdm.10183","id":10183,"links":{"badge":"https://www.fdr.uni-hamburg.de/badge/doi/10.25592/uhhfdm.10183.svg","conceptbadge":"https://www.fdr.uni-hamburg.de/badge/doi/10.25592/uhhfdm.10182.svg","conceptdoi":"http://doi.org/10.25592/uhhfdm.10182","doi":"http://doi.org/10.25592/uhhfdm.10183"},"metadata":{"access_right":"open","access_right_category":"success","communities":[{"id":"uhh"}],"creators":[{"affiliation":"Universit\u00e4t Hamburg","name":"Bruns, Patrick","orcid":"0000-0002-2977-8874"}],"description":"<p>This dataset contains data and code&nbsp;associated with the study &quot;Quantifying accuracy and precision from continuous response data in studies of spatial perception and crossmodal recalibration&quot; by Patrick Bruns, Caroline Thun, and Brigitte R&ouml;der.</p>\n\n<p><strong>example_code.R</strong> contains analysis code that can be used to&nbsp;to calculate error-based and regression-based localization performance metrics from single-subject response data with a working example in R. It requires as&nbsp;inputs&nbsp;a numeric vector containing the stimulus location (true value) in each trial and&nbsp;a numeric vector containing the corresponding localization response (perceived value) in each trial.</p>\n\n<p><strong>example_data.csv</strong> contains the data used in the working example of the analysis code.</p>\n\n<p><strong>localization.csv</strong> contains extracted localization performance metrics from 188 subjects which were analyzed in the study to assess the agreement between error-based and regression-based measures of accuracy and precision. The subjects had all naively performed an azimuthal sound localization task (see related identifiers for the underlying raw data).</p>\n\n<p><strong>recalibration.csv</strong> contains extracted localization performance metrics from a subsample of 57 subjects in whom data from a second sound localization test, performed after exposure to audiovisual stimuli in which the visual stimulus was consistently presented 13.5&deg; to the right of the sound source, were available. The file contains baseline performance (pre) and changes in performance after audiovisual exposure&nbsp;relative to baseline (delta) in each of the localization performance metrics.</p>\n\n<p>Localization performance metrics were either derived from the single-trial localization errors (error-based approach) or from a linear regression of localization responses on the actual target locations (regression-based approach).The following localization performance metrics were included in the study:</p>\n\n<p><strong>bias:</strong> overall bias of localization responses to the left (negative values) or to the right (positive values), equivalent to constant error (CE) in error-based approaches and intercept in regression-based approaches</p>\n\n<p><strong>absolute constant error (aCE):</strong> absolute value of bias (or CE), indicates the amount of bias irrespective of direction</p>\n\n<p><strong>mean absolute contant error (maCE):</strong> mean of the aCE per target location, reflects over- or underestimation of peripheral target locations</p>\n\n<p><strong>variable error (VE): </strong>mean of the standard deviations (<em>SD</em>) of the single-trial localization errors at each target location</p>\n\n<p><strong>pooled variable error (pVE):</strong>&nbsp;<em>SD</em> of the single-trial localization errors pooled across trials from all target locations</p>\n\n<p><strong>absolute error (AE):</strong> mean of the absolute values of the single-trial localization errors, sensitive to both bias and variability of the localization responses</p>\n\n<p><strong>slope: </strong>slope of the regression model function, indicates an overestimation (values &gt; 1) or underestimation (values &lt; 1) of peripheral target locations</p>\n\n<p><strong><em>R</em><sup>2</sup>: </strong>coefficient of determination of the regression model, indicates the goodness of the fit of the localization&nbsp;responses to the regression line</p>","doi":"10.25592/uhhfdm.10183","language":"eng","license":{"id":"CC-BY-4.0"},"publication_date":"2022-05-04","related_identifiers":[{"identifier":"10.25592/uhhfdm.948","relation":"references","scheme":"doi"},{"identifier":"https://osf.io/xcskn/","relation":"references","scheme":"url"},{"identifier":"10.25592/uhhfdm.10182","relation":"isVersionOf","scheme":"doi"}],"relations":{"version":[{"count":1,"index":0,"is_last":true,"last_child":{"pid_type":"recid","pid_value":"10183"},"parent":{"pid_type":"recid","pid_value":"10182"}}]},"resource_type":{"title":"Dataset","type":"dataset"},"title":"Quantifying accuracy and precision from continuous response data in studies of spatial perception and crossmodal recalibration"},"owners":[9],"revision":2,"updated":"2024-02-27T09:04:59.987338+00:00"}