ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Filtering by
- Genre: Diaries
- Genre: Fiction--Authorship.
I've intentionally chosen work that is diverse in both form and content. I have more linear fiction represented (William Trevor, for example) matched with work that's fragmentary and language focused (Christine Schutt's Nightwork among others) since I'm interested in how linear form and fragmentation can intersect, and I've been experimenting with both during my time in the program. And in terms of content, the majority of the work speaks to my interest in how region, specifically the South, impresses itself on sexuality and gender, specifically queer or decentered sexuality and gender. So I have books with a heavy focus on region (Daddy's by Lindsay Hunter and Girl Trouble by Holly Goddard Jones) and work that explores the complexities of sexuality and identity (Michael Cunningham, Edmund White, Alexander Chee, and I'll mention Haigh's film Weekend again because it's always worth mentioning again.) These works will help synthesize and bring together my interests in style, language, structure, and form, and in content.
A Monte Carlo simulation was used to generate data based on the contextual multilevel model, where sample size, effect size, and intraclass correlation (ICC) of the predictor variable were varied. The effects of simulation factors on parameter bias, parameter variability, and standard error accuracy were assessed. Parameter estimates were in general unbiased. Power to detect the slope variance and contextual effect was over 80% for most conditions, except some of the smaller sample size conditions. Type I error rates for the contextual effect were also high for some of the smaller sample size conditions. Conclusions and future directions are discussed.