Matching Items (3)
Filtering by

Clear all filters

151501-Thumbnail Image.png
Description
Daily dairies and other intensive measurement methods are increasingly used to study the relationships between two time varying variables X and Y. These data are commonly analyzed using longitudinal multilevel or bivariate growth curve models that allow for random effects of intercept (and sometimes also slope) but which do not

Daily dairies and other intensive measurement methods are increasingly used to study the relationships between two time varying variables X and Y. These data are commonly analyzed using longitudinal multilevel or bivariate growth curve models that allow for random effects of intercept (and sometimes also slope) but which do not address the effects of weekly cycles in the data. Three Monte Carlo studies investigated the impact of omitting the weekly cycles in daily dairy data under the multilevel model framework. In cases where cycles existed in both the time-varying predictor series (X) and the time-varying outcome series (Y) but were ignored, the effects of the within- and between-person components of X on Y tended to be biased, as were their corresponding standard errors. The direction and magnitude of the bias depended on the phase difference between the cycles in the two series. In cases where cycles existed in only one series but were ignored, the standard errors of the regression coefficients for the within- and between-person components of X tended to be biased, and the direction and magnitude of bias depended on which series contained cyclical components.
ContributorsLiu, Yu (Author) / West, Stephen G. (Thesis advisor) / Enders, Craig K. (Committee member) / Reiser, Mark R. (Committee member) / Arizona State University (Publisher)
Created2013
156432-Thumbnail Image.png
Description

This research conceptualizes Gothic literature featuring undead characters produced and popularized by Britain in the early nineteenth century as educational texts. As an influx of new ideas at home and abroad disrupted the lives of the Romantics, not to mention the literal uprising of bodies in the French Revolution and

This research conceptualizes Gothic literature featuring undead characters produced and popularized by Britain in the early nineteenth century as educational texts. As an influx of new ideas at home and abroad disrupted the lives of the Romantics, not to mention the literal uprising of bodies in the French Revolution and the lost war with the North American colonies, British citizens dedicated themselves to preserving the relative safety of their shores from external and internal threats. I expand the definition of the “undead” to include any tangible, corporeal being once technically dead and now reanimated. In doing so, I invite a broader range of texts, and authors, into the conversation of Gothic literature and the genre’s continued legacy. My work reads male and female authors in dialogue with one another, both sexes working within common networks, rather than as creating separate or disparate traditions. The production of instructive undead bodies becomes particularly important to the development of British national identity and reveals a reliance on the maternal to educate and inform future citizens. The texts examined in this dissertation reveal the necessity of contemplating the histories and experiences of the past, of non-white voices, and of the female influence.

The texts range in publication date from 1805 to 1863 and thus demonstrate the continued used of the undead in the Gothic genre. An examination of the reanimated corpse in Romantic narrative demonstrates how authors utilized the undead as an educational tool both for the characters inside the text and the actual individuals reading the narrative. The undead offers a lens to look at the Gothic not regarding authorial gender or even a character’s gender, but rather in how the genre portrays bodies, and how those bodies interact with and instruct others. This dissertation’s perception of the undead as a powerful educational force in literature assists in the attempt to complete a more comprehensive analysis of Gothic, and therefore Romantic, literature.

ContributorsZarka, Emily (Author) / Lussier, Mark (Thesis advisor) / Looser, Devoney (Committee member) / Broglio, Ron (Committee member) / Arizona State University (Publisher)
Created2018
154939-Thumbnail Image.png
Description
The comparison of between- versus within-person relations addresses a central issue in psychological research regarding whether group-level relations among variables generalize to individual group members. Between- and within-person effects may differ in magnitude as well as direction, and contextual multilevel models can accommodate this difference. Contextual multilevel models have been

The comparison of between- versus within-person relations addresses a central issue in psychological research regarding whether group-level relations among variables generalize to individual group members. Between- and within-person effects may differ in magnitude as well as direction, and contextual multilevel models can accommodate this difference. Contextual multilevel models have been explicated mostly for cross-sectional data, but they can also be applied to longitudinal data where level-1 effects represent within-person relations and level-2 effects represent between-person relations. With longitudinal data, estimating the contextual effect allows direct evaluation of whether between-person and within-person effects differ. Furthermore, these models, unlike single-level models, permit individual differences by allowing within-person slopes to vary across individuals. This study examined the statistical performance of the contextual model with a random slope for longitudinal within-person fluctuation data.

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.
ContributorsWurpts, Ingrid Carlson (Author) / Mackinnon, David P (Thesis advisor) / West, Stephen G. (Committee member) / Grimm, Kevin J. (Committee member) / Suk, Hye Won (Committee member) / Arizona State University (Publisher)
Created2016