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- Genre: Diaries--Psychological aspects.
- Genre: Music--Instruction and study--Korea.
- Creators: Arizona State University
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
The purpose of this study was to examine the effects of an after-school music program on music underachievers' musical achievement, social development and self-esteem. A true-experimental pretest-posttest design was used and included 14 hours of treatment time. The subjects (N = 66), fifth-grade students were randomly selected from the lowest quartile of scores on Colwell's Music Achievement Test (MAT), which was administered to all fifth-grade students (N = 494) in three Korean elementary schools. The treatment group (n =33) experienced a movement-based after-school music program (MAMP); the control group (n = 33) did not receive the after-school music program. Measurements included sections of Colwell's Music Achievement Test (MAT), Kim's Social Development Scale (SDS), and Hare's Self-Esteem Scale (HSS). The researcher and music teachers of each school administered all measurements. Fourteen treatment lessons occurred over fourteen weeks. One-way analyses of covariance tests were used to test for post-test differences between groups. A significant difference was found in music achievement total scores of the MAT with the treatment group scoring higher scores than the control group. There were no significant differences for interval and meter discrimination tests of MAT. There were no significant differences between treatment and control groups in the post-test scores of the Social Development Scale (SDS) and the Self-Esteem Scale (HSS). However, for both tests, mean scores increased for the treatment group and decreased for the control group. Results from this study suggest that a movement-based after-school music program promotes music underachievers' musical growth and may also support music underachievers' social development and self-esteem.
ContributorsYun, Gwan Ki (Author) / Stauffer, Sandra L (Thesis advisor) / Bush, Jeffrey B (Committee member) / Schmidt, Margaret T (Committee member) / Sullivan, Jill M (Committee member) / Tobias, Evan (Committee member) / Arizona State University (Publisher)
Created2011
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