The effect of noise-induced variance on parameter recovery from reaction times

BMC Bioinformatics

Methodology Article

Pablo Garaizar¹  Miguel A. Vadillo² 

[1] Faculty of Engineering, Universidad de Deusto, Avda. Universidades 24, 48007, Bilbao, Spain;Primary Care and Public Health Sciences, King’s College London, Addison House, Guy’s Campus, SE1 1UL, London, UK;Division of Psychology and Language Sciences, University College London, 26 Bedford Way, WC1H 0AH, London, UK;

关键词: ex-Gaussian distribution;    Internet-based experiments;    Model fitting;    Psychological experiments;    Ratcliff Diffusion Model;    Reaction times;   

DOI  :  10.1186/s12859-016-0993-x

 received in 2016-01-19, accepted in 2016-03-17,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundTechnical noise can compromise the precision and accuracy of the reaction times collected in psychological experiments, especially in the case of Internet-based studies. Although this noise seems to have only a small impact on traditional statistical analyses, its effects on model fit to reaction-time distributions remains unexplored.ResultsAcross four simulations we study the impact of technical noise on parameter recovery from data generated from an ex-Gaussian distribution and from a Ratcliff Diffusion Model. Our results suggest that the impact of noise-induced variance tends to be limited to specific parameters and conditions.ConclusionsAlthough we encourage researchers to adopt all measures to reduce the impact of noise on reaction-time experiments, we conclude that the typical amount of noise-induced variance found in these experiments does not pose substantial problems for statistical analyses based on model fitting.

【 授权许可】

CC BY   
© Vadillo and Garaizar. 2016