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Exploring the persome: The power of the item in understanding personality structure

Authors :
Elizabeth M. Dworak
William Revelle
David M. Condon
Source :
Personality and Individual Differences. 169:109905
Publication Year :
2021
Publisher :
Elsevier BV, 2021.

Abstract

We discuss methods of data collection and analysis that emphasize the power of individual personality items for predicting real world criteria (e.g., smoking, exercise, self-rated health). These methods are borrowed by analogy from radio astronomy and human genomics. Synthetic Aperture Personality Assessment (SAPA) applies a matrix sampling procedure that synthesizes very large covariance matrices through the application of massively missing at random data collection. These large covariance matrices can be applied, in turn, in Persome Wide Association Studies (PWAS) to form personality prediction scores for particular criteria. We use two open source data sets (N=4,000 and 126,884 with 135 and 696 items respectively) for demonstrations of both of these procedures. We compare these procedures to the more traditional use of “Big 5” or a larger set of narrower factors (the “little 27”). We argue that there is more information at the item level than is used when aggregating items to form factorially derived scales.

Details

ISSN :
01918869
Volume :
169
Database :
OpenAIRE
Journal :
Personality and Individual Differences
Accession number :
edsair.doi...........60217329503aceea5c0a4b16f1055e5f
Full Text :
https://doi.org/10.1016/j.paid.2020.109905