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- Genre: Diaries
- Genre: Art--Study and teaching (Secondary)--Arizona.
- Creators: Arizona State University
- Member of: Theses and Dissertations
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 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
Description
Many alternative schools for at-risk students do not offer art classes to their students. Phoenix Job Corps is one of those schools. I conducted a qualitative study about a voluntary summer art course at Phoenix Job Corps, a vocational school for at-risk students. I had thirteen student volunteers, eight of them refugees from other countries. All the participants created a narrative painting about something in their lives. The purpose of this study was to examine this voluntary summer art course and to determine its usefulness as a beneficial tool to the lives of the students. This included looking at participants' narrative paintings to determine common themes or subjects, finding out their opinions on whether or not their school should offer an art course, their willingness to share their stories, determining whether they think it's important for others to see their work, and lastly concluding what artwork they like best and why. I found that the majority of students do want an art class offered at their schools, and all but one participant was more than willing to share their story about their narrative painting. Common themes amongst their paintings were family, a specific memory or event, or their present and future lives. I found similar subject matter in their paintings such as animals, houses or huts, and people. My research also unveiled a large difference in the refugee students' paintings as opposed to the other United States participants. The findings also suggest that participants judged other work based on meaning more so than aesthetics. This study explores, in detail, the narrative art and experiences of a very diverse group of students.
ContributorsSchaller, Kimberly (Author) / Young, Bernard (Thesis advisor) / Erickson, Mary (Committee member) / Stokrocki, Mary (Committee member) / Arizona State University (Publisher)
Created2012
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 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.
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