The visual world paradigm is a tool that is widely used in the field of psycholinguistics to help investigate how people listen and understand words and sentences. Proportions of fixations to several different objects are recorded for a number of subjects, over a specific time period. Researchers have found it difficult to find models that can incorporate multiple random effects, account for the correlated nature of the data, and simultaneously fit multiple fixation curves/groups. We have taken a Bayesian hierarchical modeling approach for this multivariate non-linear longitudinal data. Within in this framework, we look at both parametric and nonparametric approaches in simultaneously modeling multiple curves. Finally, we will look at different comparison techniques to compare these curves under a Bayesian framework.
| Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-7086 |
| Date | 01 May 2016 |
| Creators | Pugh, Melissa Anna Maria |
| Contributors | Oleson, Jacob J. |
| Publisher | University of Iowa |
| Source Sets | University of Iowa |
| Language | English |
| Detected Language | English |
| Type | dissertation |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | Copyright © 2016 Melissa Anna Maria Pugh |
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