Please use this identifier to cite or link to this item: https://doi.org/10.3389/fpsyg.2016.00738
Title: Analyzing big data in psychology: A split/analyze/meta-analyze approach
Authors: Cheung, M.W.-L 
Jak, S 
Issue Date: 2016
Publisher: Frontiers Media S.A.
Citation: Cheung, M.W.-L, Jak, S (2016). Analyzing big data in psychology: A split/analyze/meta-analyze approach. Frontiers in Psychology 7 (MAY) : 738. ScholarBank@NUS Repository. https://doi.org/10.3389/fpsyg.2016.00738
Abstract: Big data is a field that has traditionally been dominated by disciplines such as computer science and business, where mainly data-driven analyses have been performed. Psychology, a discipline in which a strong emphasis is placed on behavioral theories and empirical research, has the potential to contribute greatly to the big data movement. However, one challenge to psychologists-and probably the most crucial one-is that most researchers may not have the necessary programming and computational skills to analyze big data. In this study we argue that psychologists can also conduct big data research and that, rather than trying to acquire new programming and computational skills, they should focus on their strengths, such as performing psychometric analyses and testing theories using multivariate analyses to explain phenomena. We propose a split/analyze/meta-analyze approach that allows psychologists to easily analyze big data. Two real datasets are used to demonstrate the proposed procedures in R. A new research agenda related to the analysis of big data in psychology is outlined at the end of the study. © 2016 Cheung and Jak.
Source Title: Frontiers in Psychology
URI: https://scholarbank.nus.edu.sg/handle/10635/174268
ISSN: 16641078
DOI: 10.3389/fpsyg.2016.00738
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