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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.

Although the measurement of intelligence is important, researchers sometimes avoid using them in their studies due to their history, cost, or burden on the researcher. To encourage the use of cognitive ability items in research, we discuss the development and validation of the International Cognitive Ability Resource (ICAR), a growing set of items from 19 different subdomains. We consider how these items might benefit open science in contrast to more established proprietary measures. A short summary of how these items have been used in outside studies is provided in addition to ways we would love to see the use of public-domain cognitive ability items grow.

article i nfo The ability to locate and orient ourselves with respect to environmental space is known as sense of direction ("SOD"). While there is considerable evidence for the predictive utility of self-report measures of this psycholog- ical construct, relatively little research has investigated the psychometric properties of the self-report scale by which it is most commonly measured - the Santa Barbara Sense of Direction scale (SBSOD, Hegarty et al., 2002) - or the broader personality correlates. The present study evaluated the factor structure of the SBSOD fol- lowing administration to 12,155 individuals and situated it among prominent sources of individual differences, specifically the Big Five personality traits and intelligence. Findings suggest that the SBSOD scale has relatively high general factor saturation, and that a considerable portion of the variance in SBSOD scores is explained by other personality traits, including Conscientiousness (r = 0.33), Intellect (r = 0.27), Emotional Stability (r = 0.26), and Extraversion (r = 0.23). Cognitive ability was less highly correlated with SBSOD scores when mea- sured at the level of general intelligence (r = 0.11) and in terms of mental rotation ability (r = .07). Recommen- dations are given for revision of the SBSOD scale based on item-level analyses.

For all of its versatility and sophistication, the extant toolkit of cognitive ability measures lacks a public-domain method for large-scale, remote data collection. While the lack of copyright protection for such a measure poses a theoretical threat to test validity, the effective magnitude of this threat is unknown and can be offset by the use of modern test-development techniques. To the extent that validity can be maintained, the benefits of a public-domain resource are considerable for researchers, including: cost savings; greater control over test content; and the potential for more nuanced understanding of the correlational structure between constructs. The International Cognitive Ability Resource was developed to evaluate the prospects for such a public-domain measure and the psychometric properties of the first four item types were evaluated based on administrations to both an offline university sample and a large online sample. Concurrent and discriminative validity analyses suggest that the public-domain status of these item types did not compromise their validity despite administration to 97,000 participants. Further development and validation of extant and additional item types are recommended.

Personality is an abstraction used to describe and explain the coherent patterning over time and space of affect, cognition, and desire as they result in behaviour for an individual. This unique patterning or individual signature reflects a complex set of dynamic processes that can be modelled in terms of rates of growth and decay of excitation and inhibition in response to environmental cues. These processes reflect genetically based biological sensitivities that may be modelled by the differential equations of the Dynamics of Action. The important parameters within individuals reflect rates of change; the important parameters between individuals reflect average levels, frequencies and persistence. Going beyond models within and between individuals, it is also necessary to consider how individuals choose their environments. We will consider how analyses of these three levels (within individuals, between individuals, and between groups of individuals) can lead to different descriptions about the structure and processes of personality.

A prominent goal of individual differences research is the development and testing of models which predict important life outcomes. Prior work suggests that the most predictive models for many outcomes integrate multiple dimensions of individual differences and that three of the most informative dimensions are temperament, cognitive abilities and interests. Of these three, large-scale assessment of cognitive abilities has been the most problematic due to methodological constraints. Recent and ongoing development of the public-domain International Cognitive Ability Resource is intended to address these constraints. In this talk, we will describe the procedures being used to develop this resource and summarize progress to date. Then, using online data collected with synthetic aperture personality assessment (”SAPA”) methods (sapa-project.org), we compare the predictive utility of integrated individual difference models against those which use only the independent dimensions (of temperament or interests or ability) in the context of academic, occupational and health outcomes.