| Literature DB >> 20160294 |
Alec Solway1, Aaron S Geller, Per B Sederberg, Michael J Kahana.
Abstract
Studies of human memory often generate data on the sequence and timing of recalled items, but scoring such data using conventional methods is difficult or impossible. We describe a Python-based semiautomated system that greatly simplifies this task. This software, called PyParse, can easily be used in conjunction with many common experiment authoring systems. Scored data is output in a simple ASCII format and can be accessed with the programming language of choice, allowing for the identification of features such as correct responses, prior-list intrusions, extra-list intrusions, and repetitions.Entities:
Mesh:
Year: 2010 PMID: 20160294 PMCID: PMC2828933 DOI: 10.3758/BRM.42.1.141
Source DB: PubMed Journal: Behav Res Methods ISSN: 1554-351X