Methods for validating chronometry of computerized tests.
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| Title: | Methods for validating chronometry of computerized tests. |
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| Authors: | Salmon, Joshua P. (AUTHOR), Jones, Stephanie A. H. (AUTHOR), Wright, Chris P. (AUTHOR), Butler, Beverly C. (AUTHOR), Klein, Raymond M. (AUTHOR), Eskes, Gail A. (AUTHOR) |
| Source: | Journal of Clinical & Experimental Neuropsychology. Mar2017, Vol. 39 Issue 2, p190-210. 21p. |
| Subjects: | Time perception, Reaction time, Psychophysiology, Motor ability, Neuropsychological tests |
| Abstract: | Determining the speed at which a task is performed (i.e., reaction time) can be a valuable tool in both research and clinical assessments. However, standard computer hardware employed for measuring reaction times (e.g., computer monitor, keyboard, or mouse) can add nonrepresentative noise to the data, potentially compromising the accuracy of measurements and the conclusions drawn from the data. Therefore, an assessment of the accuracy and precision of measurement should be included along with the development of computerized tests and assessment batteries that rely on reaction times as the dependent variable. This manuscript outlines three methods for assessing the temporal accuracy of reaction time data (one employing external chronometry). Using example data collected from the Dalhousie Computerized Attention Battery (DalCAB) we discuss the detection, measurement, and correction of nonrepresentative noise in reaction time measurement. The details presented in this manuscript should act as a cautionary tale to any researchers or clinicians gathering reaction time data, but who have not yet considered methods for verifying the internal chronometry of the software and or hardware being used. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Clinical & Experimental Neuropsychology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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