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The last two decades have seen growing awareness of and emphasis on the replication of empirical findings. While this is a large literature, very little of it has focused on or considered the interaction of replication and psychometrics. This is unfortunate given that sound measurement is crucial when considering the complex constructs studied in psychological research. If the psychometric properties of a scale fail to replicate, then inferences made using scores from that scale are questionable at best. In this dissertation, I begin to address replication issues in factor analysis – a widely used psychometric method in psychology. After noticing inconsistencies across results for studies that factor analyzed the same scale, I sought to gain a better understanding of what replication means in factor analysis as well as address issues that affect the replicability of factor analytic models. With this work, I take steps toward integrating factor analysis into the broader replication discussion. Ultimately, the goal of this dissertation was to highlight the importance of psychometric replication and bring attention to its role in fostering a more replicable scientific literature.
ContributorsManapat, Patrick D. (Author) / Edwards, Michael C. (Thesis advisor) / Anderson, Samantha F. (Thesis advisor) / Grimm, Kevin J. (Committee member) / Levy, Roy (Committee member) / Arizona State University (Publisher)
Created2022
Description
Previous research used the context-free Big Five model of personality traits to predict social media behaviors. The perspective implicit in this research assumes that expression of the Big Five is free of situational context. This thesis challenges this assumption to address whether people express the same Big Five on social media as offline. In two studies, this thesis addressed three issues: (1) whether there are self-reported differences in the Big Five between social media/online and offline contexts, (2) whether a five-factor structure replicates in the offline and social media context reports, and (3) whether the predictive validity of the Big Five is the same between offline and social media contexts. College students (total N = 2102) reported their offline and social media Big Five. Main findings reveal that, first, all of the Big Five have lower expressions in social media/online than offline, except for those in the lowest quartile of offline trait expressions; possible explanations include regression towards the mean or the environmental impact of social media. Second, a similar factor structure appeared with openness, extraversion, and neuroticism items being the most robust between offline and social media contexts. However, some conscientiousness and agreeableness items did not apply across offline and social media contexts. Third, the Big Five had different predictive patterns of social media behaviors depending on the context. These findings inform that future research may better serve to specify the context of Big Five expression to understand social media behavior.
ContributorsBunker, Cameron James (Author) / Kwan, Virginia S. Y. (Thesis advisor) / Edwards, Michael C. (Committee member) / Kenrick, Douglas T. (Committee member) / Arizona State University (Publisher)
Created2020