Bayesian Analysis of Individual Level Personality Dynamics
AuthorCripps, E; Wood, RE; Beckmann, N; Lau, J; Beckmann, JF; Cripps, SA
Source TitleFrontiers in Psychology
PublisherFRONTIERS MEDIA SA
University of Melbourne Author/sWood, Robert
Document TypeJournal Article
CitationsCripps, E., Wood, R. E., Beckmann, N., Lau, J., Beckmann, J. F. & Cripps, S. A. (2016). Bayesian Analysis of Individual Level Personality Dynamics. FRONTIERS IN PSYCHOLOGY, 7 (JUL), https://doi.org/10.3389/fpsyg.2016.01065.
Access StatusOpen Access
A Bayesian technique with analyses of within-person processes at the level of the individual is presented. The approach is used to examine whether the patterns of within-person responses on a 12-trial simulation task are consistent with the predictions of ITA theory (Dweck, 1999). ITA theory states that the performance of an individual with an entity theory of ability is more likely to spiral down following a failure experience than the performance of an individual with an incremental theory of ability. This is because entity theorists interpret failure experiences as evidence of a lack of ability which they believe is largely innate and therefore relatively fixed; whilst incremental theorists believe in the malleability of abilities and interpret failure experiences as evidence of more controllable factors such as poor strategy or lack of effort. The results of our analyses support ITA theory at both the within- and between-person levels of analyses and demonstrate the benefits of Bayesian techniques for the analysis of within-person processes. These include more formal specification of the theory and the ability to draw inferences about each individual, which allows for more nuanced interpretations of individuals within a personality category, such as differences in the individual probabilities of spiraling. While Bayesian techniques have many potential advantages for the analyses of processes at the level of the individual, ease of use is not one of them for psychologists trained in traditional frequentist statistical techniques.
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