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

• Published in: BMC bioinformatics Vol. 17; no. 1; p. 147
• Main Authors: Vadillo, Miguel A., Garaizar, Pablo
• Format: Journal Article
• Language: English
• Published: London BioMed Central 31.03.2016; BioMed Central Ltd; Springer Nature B.V
• Subjects: Algorithms; Analysis; Bioinformatics; Biomedical and Life Sciences; Computational biology; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Diagnostic Imaging; Life Sciences; Methodology; Methodology Article; Microarrays; Models, Theoretical; Noise control; Normal Distribution; Reaction Time; Results and data; Statistical analysis; United Kingdom; Psychological experiments; Ratcliff Diffusion Model; Reaction times; Model fitting; Internet-based experiments; ex-Gaussian distribution
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-016-0993-x

Background Technical 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. Results Across 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. Conclusions Although 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.