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- All Subjects: nonwork role priority
- Genre: Doctoral Dissertation
- Creators: Green, Samuel
Description
This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex performance assessment within a digital-simulation educational context grounded in theories of cognition and learning. BN models were manipulated along two factors: latent variable dependency structure and number of latent classes. Distributions of posterior predicted p-values (PPP-values) served as the primary outcome measure and were summarized in graphical presentations, by median values across replications, and by proportions of replications in which the PPP-values were extreme. An effect size measure for PPMC was introduced as a supplemental numerical summary to the PPP-value. Consistent with previous PPMC research, all investigated fit functions tended to perform conservatively, but Standardized Generalized Dimensionality Discrepancy Measure (SGDDM), Yen's Q3, and Hierarchy Consistency Index (HCI) only mildly so. Adequate power to detect at least some types of misfit was demonstrated by SGDDM, Q3, HCI, Item Consistency Index (ICI), and to a lesser extent Deviance, while proportion correct (PC), a chi-square-type item-fit measure, Ranked Probability Score (RPS), and Good's Logarithmic Scale (GLS) were powerless across all investigated factors. Bivariate SGDDM and Q3 were found to provide powerful and detailed feedback for all investigated types of misfit.
ContributorsCrawford, Aaron (Author) / Levy, Roy (Thesis advisor) / Green, Samuel (Committee member) / Thompson, Marilyn (Committee member) / Arizona State University (Publisher)
Created2014
Description
Individuals are attracted to occupational environments that align with their interests and personality characteristics (Holland, 1985, 1997). When an individual's attributes (i.e., needs, abilities, values and/or interests) align with the occupational environment's characteristics an individual is more satisfied. Past research suggests this relation is modest at best, hovering between .20 and .30 (Meyer et al., 2001, c.f. Wilkins & Tracey, 2014), with slightly higher estimates (ranging from .24 to .35) depending on how the variables of person and environment were measured (Kristof-Brown, Zimmerman, & Johnson, 2005). Several factors contribute to such low estimates, most notably the role of moderator variables in suppressing or exacerbating the true magnitude of this relation. A moderator that has yet to be explored is that of nonwork role priority, or the degree to which an individual's work identity is valued relative to other role identities. In the current study, three hypotheses were posited to investigate nonwork role priorities as a potential moderator to the congruence-satisfaction relation. Latent class analysis was used to apply a person-centered approach to understanding response patterns and differences in these roles. The sample was differentiated best by a two-class solution and the class variable in all three hierarchical regression models explained about five percent of the variance in job satisfaction, which suggests that work and nonwork role priority are meaningful to understanding individual career happiness. Class was not identified as a significant moderator to the congruence-satisfaction relation. Discussion of limitations to the current study and recommendations for future work in this area are presented.
ContributorsKube, Erin (Author) / Tracey, Terence J. (Thesis advisor) / Green, Samuel (Committee member) / Thompson, Marilyn (Committee member) / Arizona State University (Publisher)
Created2016