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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
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Description
This research paper examines Guillaume Lekeu's Sonata for Piano and Violin (1892) from the perspective of a collaborative pianist, providing historical background, an analysis of the work's musical structure, and performance practice insights. Each chapter offers the performer a deeper understanding of various aspects concerning the work, including an in-depth

This research paper examines Guillaume Lekeu's Sonata for Piano and Violin (1892) from the perspective of a collaborative pianist, providing historical background, an analysis of the work's musical structure, and performance practice insights. Each chapter offers the performer a deeper understanding of various aspects concerning the work, including an in-depth analysis of cyclical features used by Lekeu.

Lekeu was strongly influenced by his teacher, César Franck, and in particular by Franck's use of cyclic techniques, which profoundly impacted Lekeu's Sonata for Piano and Violin. The cyclic treatment, which includes cyclic themes, cyclic motives, and non-cyclic themes is discussed, enabling performers to achieve a relevant structural approach to this work. A performance guide includes practical advice for the interpretation and performance of the work, along with piano pedaling suggestions. The integration of these aspects enables a pianist to gain a better understanding and appreciation of Lekeu's Sonata for Piano and Violin.
ContributorsZhang, Dongfang (Author) / Ryan, Russell (Thesis advisor) / Campbell, Andrew (Committee member) / Rogers, Rodney (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Charles-Valentin Alkan’s Grande Sonate Op. 33 ‘Les quatre âges’ is a unique four-movement work for piano solo that programmatically represents a man’s life through four decades, passing from age 20 to 50, with each movement being progressively slower than the previous. Published in 1847, it was destined for obscurity

Charles-Valentin Alkan’s Grande Sonate Op. 33 ‘Les quatre âges’ is a unique four-movement work for piano solo that programmatically represents a man’s life through four decades, passing from age 20 to 50, with each movement being progressively slower than the previous. Published in 1847, it was destined for obscurity until it was rediscovered and premiered in 1973 by English pianist Ronald Smith. Its absence from the public’s reach can be attributed to multiple reasons including the reclusive nature of the composer during the time of composition and the societal issues surrounding the French Revolution of 1848.

Much of Alkan’s music has a reputation for being nearly unplayable because of its complexity and the extremely high level of technical facility a pianist must possess in order to perform it convincingly. Aside from its performance length of nearly an hour, there are many technical issues that prevent Alkan’s Grande Sonate from being performed more frequently. This paper is an exploration of some of these performance and technical issues for consideration by pianists interested in solving the riddle of performing Alkan’s Grande Sonate.

The findings explored are based in part on the author’s experience in performing the complete Grande Sonate in recital, as well as on extant research into Alkan’s life and the interpretation and performance of his works. The paper concludes with an appendix and link to the author’s live performance of the work, another appendix renotating the fugato from Quasi-Faust, and a third appendix providing extensive fingering and voice redistribution for Les enfans [sic] from 40 ans.
ContributorsHillmann, Joshua Lester (Author) / Meir, Baruch (Thesis advisor) / Pagano, Caio (Committee member) / Hamilton, Robert (Committee member) / Rockmaker, Jody (Committee member) / Arizona State University (Publisher)
Created2018
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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