Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/25531
Appears in Collections:Management, Work and Organisation Journal Articles
Peer Review Status: Refereed
Title: Modeling bivariate change in individual differences: Prospective associations between personality and life satisfaction (Forthcoming/Available Online)
Authors: Hounkpatin, Hilda Osafo
Boyce, Christopher J
Dunn, Graham
Wood, Alex M
Keywords: personality
individual differences
life satisfaction
latent change score model
structural equation models
Issue Date: 18-Sep-2017
Citation: Hounkpatin HO, Boyce CJ, Dunn G & Wood AM (2017) Modeling bivariate change in individual differences: Prospective associations between personality and life satisfaction (Forthcoming/Available Online), Journal of Personality and Social Psychology.
Abstract: A number of structural equation models have been developed to examine change in one variable or the longitudinal association between two variables. The most common of these are the latent growth model, the autoregressive cross-lagged model, the autoregressive latent trajectory model, and the latent change score model. We first overview each of these models through evaluating their different assumptions surrounding the nature of change and how these assumptions may result in different data interpretations. We then, to elucidate these issues in an empirical example, examine the longitudinal association between personality traits and life satisfaction. In a representative Dutch sample (N = 8320), with participants providing data on both personality and life satisfaction measures every two years over an eight year period, we reproduce findings from previous research. However, some of the structural equation models overviewed have not previously been applied to the personality-life satisfaction relation. Our extended empirical examination suggests intra-individual changes in life satisfaction predict subsequent intra-individual changes in personality traits. The availability of datasets with three or more assessment waves allows the application of more advanced structural equation models such as the autoregressive latent trajectory or the extended latent change score model, which accounts for the complex dynamic nature of change processes and allows stronger inferences on the nature of the association between variables. However, the choice of model should be determined by theories of change processes in the variables being studied.
DOI Link: http://dx.doi.org/10.1037/pspp0000161
Rights: This article has been published under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright for this article is retained by the author(s). Author(s) grant(s) the American Psychological Association the exclusive right to publish the article and identify itself as the original publisher.

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