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Introduction to the special issue on recentering science: Replication, robustness, and reproducibility in psychophysiology
Author(s) -
Kappenman Emily S.,
Keil Andreas
Publication year - 2017
Publication title -
psychophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.661
H-Index - 156
eISSN - 1469-8986
pISSN - 0048-5772
DOI - 10.1111/psyp.12787
Subject(s) - psychophysiology , multidisciplinary approach , psychology , field (mathematics) , robustness (evolution) , variety (cybernetics) , data science , management science , neuroscience , computer science , artificial intelligence , social science , biochemistry , chemistry , mathematics , sociology , pure mathematics , economics , gene
In recent years, the psychological and behavioral sciences have increased efforts to strengthen methodological practices and publication standards, with the ultimate goal of enhancing the value and reproducibility of published reports. These issues are especially important in the multidisciplinary field of psychophysiology, which yields rich and complex data sets with a large number of observations. In addition, the technological tools and analysis methods available in the field of psychophysiology are continually evolving, widening the array of techniques and approaches available to researchers. This special issue presents articles detailing rigorous and systematic evaluations of tasks, measures, materials, analysis approaches, and statistical practices in a variety of subdisciplines of psychophysiology. These articles highlight challenges in conducting and interpreting psychophysiological research and provide data‐driven, evidence‐based recommendations for overcoming those challenges to produce robust, reproducible results in the field of psychophysiology.