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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Ethnic differences in achievement growth: Longitudinal data analysis of math achievement in a hierarchical linear modeling framework

Xiang, Yun January 2009 (has links)
Thesis advisor: Henry Braun / Given the call for greater understanding of racial inequality in student achievement in K-12 education, this study contributes a comprehensive, quantitative, longitudinal examination of the achievement gap phenomenon, with particular attention to the organization characteristics of schools and school districts. Employing data from a large number of districts in a single state, it examines the trends in achievement and the growth in achievement after the passage of NCLB. It focuses on mathematics performance from grade 6 to grade 8. Both a traditional descriptive approach and one employing Hierarchical Linear Models were applied and compared. The purpose was not to determine which methodology is superior but to provide complementary perspectives. The comparison between the two approaches revealed similar trends in achievement gaps, but the HLM approach offered a more nuanced description. Nonetheless the results suggest that it is useful to employ both approaches. As to the main question regarding ethnicity, it appears that even if student ethnicity is confounded with other indicators, such as initial score and socio-economic status, it is still an important predictor of both achievement gaps and achievement growth gaps. Moreover, demographic profiles at the school and district levels were also associated with these gaps. / Thesis (PhD) — Boston College, 2009. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement, and Evaluation.
2

Integrating Health Education and Leisure Time into Economic Growth Modeling

Rollo, Sara K. 23 December 2009 (has links)
No description available.
3

Adolescent Self-Regulation and the Influence of Peer Victimization: Examining Dynamic Interactions

Knoble, Naomi 18 August 2015 (has links)
Self-regulation is essential for successful social functioning, yet more remains to be understood about the influence of peers on this important developmental skill. This study examined the influence of verbal peer victimization on the growth of self-regulation across four years of early adolescence using parallel process growth modeling. For all adolescents, higher levels of self-regulation buffered early adolescents from the effects of negative peer interactions. In addition, early adolescents with initially low levels of self-regulation also had higher levels of depression and experienced higher levels of peer victimization than their better regulated peers. Importantly the Family Check-Up, a brief preventative intervention, resulted in improvements in self-regulation that was sustained over time. The relationship between peer victimization and self-regulation was not predictive; however, a significant persisting association was observed suggesting that improvements in adolescent self-regulation abilities help buffer youth from the impact of negative peer interactions. This research highlights the importance of the social context on the development of self-regulation during adolescence and contributes novel findings of the effect of contextual variables on self-regulation development. These findings support an ecological prevention approach, including family-centered intervention and social-emotional curricula, to promote increased self-regulation and reduce peer victimization among adolescents.
4

Linear Mixed-Effects Models: Applications to the Behavioral Sciences and Adolescent Community Health

Maldonado, Lizmarie Gabriela 01 January 2012 (has links)
Linear mixed-effects (LME) modeling is a widely used statistical method for analyzing repeated measures or longitudinal data. Such longitudinal studies typically aim to investigate and describe the trajectory of a desired outcome. Longitudinal data have the advantage over cross-sectional data by providing more accuracy for the model. LME models allow researchers to account for random variation among individuals and between individuals. In this project, adolescent health was chosen as a topic of research due to the many changes that occur during this crucial time period as a precursor to overall well-being in adult life. Understanding the factors that influence how adolescents' mental well-being is affected may aid in interventions to reduce the risk of a negative impact. Self-esteem, in particular, has been associated with many components of physical and mental health and is a crucial focus in adolescent health. Research in self-esteem is extensive yet, sometimes inconclusive or contradictory since past research has been cross-sectional in nature. Several factors associated with self-esteem development are considered. Participation in religious services has also been an interest in research for its impact on depression. Depression development and its predictors are evaluated using LME models. Along with this line, this project will address the research problems identified through the following specific topics (i) to investigate the impact of early adolescent anxiety disorders on self-esteem development from adolescence to young adulthood; (ii) to study the role of maternal self-esteem and family socioeconomic status on adolescent self-esteem development through young adulthood; and (iii) to explore the efficacy of religious service attendance in reducing depressive symptoms. These topics present a good introduction to the LME approach and are of significant public health importance. The present study explores varying scenarios of the statistical methods and techniques employed in the analysis of longitudinal data. This thesis provides an overview of LME models and the model selection process with applications. Although this project is motivated by adolescent health study, the basic concepts of the methods introduced have generally broader applications in other fields provided that the relevant technical specifications are met.
5

Shared Leadership: Experimental Evidence On Its Antecedents and Impact on Team Outcomes

Huang, Shujing 15 April 2010 (has links)
Leadership has been traditionally conceptualized as individual-centered and top-down. However, the fast growing environment creates demands beyond the capabilities of an individual leader and requires flexible and adaptive leadership structures in response. The current study built upon research in leadership and teams and employed an iterative experimental design to investigate the emergence of shared leadership through its antecedents (i.e., power structure and role assignment) and examine its impact on team outcomes (i.e., productivity, adaptability and innovation). The relationship between shared leadership and other team properties (i.e., collective efficacy and team cohesiveness) were also scrutinized. Social network analysis (SNA) and growth modeling techniques were utilized. Support for hypotheses was not found. Methodological and analytical limitations and future research directions were discussed. / Master of Science
6

A Longitudinal analysis investigating the role of immigrant generation status on intra-linguistic and cross-linguistic models of reading comprehension among Latino bilinguals in elementary school

Leider, Christine Montecillo January 2015 (has links)
Thesis advisor: C. Patrick Proctor / The role of immigrant generation status on Latinos' English language development has not received much attention. Empirical studies (Bean & Stevens, 2003) and descriptive data (Fry & Passal, 2009), suggest an intergenerational shift from Spanish to English, such that the first generation primarily speaks Spanish, the second generation speaks both Spanish and English, and the third generation primarily speaks English. Indeed, this intergenerational shift suggests the important role of immigrant generation status in the language and reading comprehension development of bilingual Latinos. If first generation students are more likely to be Spanish dominant, arguably their English language and reading development are likely to be distinctive from their American born peers. Logically, this would suggest a lockstep intergenerational improvement such that second and third generation peers would significantly outperform the first generation in English language and reading. To address this role of immigrant status in the English language and reading development among Latino bilinguals, this dissertation is divided into two studies. The first study was guided by a component view of reading within the context of the immigrant paradox. The second study was concerned with the role of immigrant generation status on the linguistic interdependence (Cummins, 1979) between Spanish language, English language, and English reading comprehension. Both studies utilized multi-level growth modeling to develop longitudinal growth trajectories of English language and reading development. Results indicated that Latino children's English language and reading comprehension performance increased over time. For Study 1, significant effects for generation status suggested a Generation 2 and Generation 3 advantage. For Study 2, significant effects for generation status and Spanish language on the English language growth trajectories provide evidence for paradoxical immigrant generation status trends and cross-language transfer. Both studies emphasize the need for educators to be cognizant of linguistic differences within the bilingual population - particularly for newcomers and students who are less likely to speak English. / Thesis (PhD) — Boston College, 2015. / Submitted to: Boston College. Lynch School of Education. / Discipline: Teacher Education, Special Education, Curriculum and Instruction.
7

Geographies of motherhood : sub-national differences in the involvement in paid work of mothers of young children : the cases of Germany and the UK

Walthery, Pierre January 2012 (has links)
In this thesis I analyse sub-national differences in the employment trajectories of mothers of young children in Germany (Bundeslaender) and the UK (Government Office Regions and Metropolitan counties). The thesis combines longitudinal and spatial approaches to paid work, and focuses on mothers of children under 6 - arguably the group at the core of the social (re)production of gender differences in employment. One of its aims is to nuance the existing literature explaining the differences in women's involvement in paid work in terms of national welfare and/or breadwinner regimes - by looking at the nature and extent of regional variations in the patterns of involvement that make these countries typical of such regimes. Its specific goals consist in testing the Latent Growth Curve (LCM) framework as a method for modelling variations in participation in paid work over time, then in exploring three possible explanations for the regional differences observed. The respective role of regional differences in the family formation and social position of the maternal labour force, of the availability of suitable jobs in particular segregated jobs, and finally of economic histories in relation to women's orientations to work is assessed. The results confirmed that LCM represents an innovative tool to understand variations of involvement in paid work over time, and revealed significant regional differences, beyond the 'North South' and 'East-West' divides documented respectively in the UK and Germany. In both countries, results pointed at a combined effect of the three explanatory factors analysed. Whilst composition and labour demands effects went some way towards explaining some of the variations observed, at the same time additional regional variations were discovered once composition factors were taken into account. Finally the pattern of association between the remaining unexplained regional variation and aggregate attitudes of women towards paid work suggests an influence of long term trends in participation on present levels of involvement.
8

Examination of Mixed-Effects Models with Nonparametrically Generated Data

January 2019 (has links)
abstract: Previous research has shown functional mixed-effects models and traditional mixed-effects models perform similarly when recovering mean and individual trajectories (Fine, Suk, & Grimm, 2019). However, Fine et al. (2019) showed traditional mixed-effects models were able to more accurately recover the underlying mean curves compared to functional mixed-effects models. That project generated data following a parametric structure. This paper extended previous work and aimed to compare nonlinear mixed-effects models and functional mixed-effects models on their ability to recover underlying trajectories which were generated from an inherently nonparametric process. This paper introduces readers to nonlinear mixed-effects models and functional mixed-effects models. A simulation study is then presented where the mean and random effects structure of the simulated data were generated using B-splines. The accuracy of recovered curves was examined under various conditions including sample size, number of time points per curve, and measurement design. Results showed the functional mixed-effects models recovered the underlying mean curve more accurately than the nonlinear mixed-effects models. In general, the functional mixed-effects models recovered the underlying individual curves more accurately than the nonlinear mixed-effects models. Progesterone cycle data from Brumback and Rice (1998) were then analyzed to demonstrate the utility of both models. Both models were shown to perform similarly when analyzing the progesterone data. / Dissertation/Thesis / Doctoral Dissertation Psychology 2019
9

Model Specification Searches in Latent Growth Modeling: A Monte Carlo Study

Kim, Min Jung 2012 May 1900 (has links)
This dissertation investigated the optimal strategy for the model specification search in the latent growth modeling. Although developing an initial model based on the theory from prior research is favored, sometimes researchers may need to specify the starting model in the absence of theory. In this simulation study, the effectiveness of the start models in searching for the true population model was examined. The four possible start models adopted in this study were: the simplest mean and covariance structure model, the simplest mean and the most complex covariance structure model, the most complex mean and the simplest covariance structure model, and the most complex mean and covariance structure model. Six model selection criteria were used to determine the recovery of the true model: Likelihood ratio test (LRT), DeltaCFI, DeltaRMSEA, DeltaSRMR, DeltaAIC, and DeltaBIC. The results showed that specifying the most complex covariance structure (UN) with the most complex mean structure recovered the true mean trajectory most successfully with the average hit rate above 90% using the DeltaCFI, DeltaBIC, DeltaAIC, and DeltaSRMR. In searching for the true covariance structure, LRT, DeltaCFI, DeltaAIC, and DeltaBIC performed successfully regardless of the searching method with different start models.
10

Emerging Paths to Literacy: Modeling Individual and Environmental Contributions to Growth in Children's Emergent Literacy Skills

Swan, Deanne W 02 January 2009 (has links)
What is the developmental trajectory of the skills that underlie emergent literacy during the preschool years? Are there individual characteristics which predict whether a child will be at-risk for difficulties in acquiring literacy skills? Does a child’s experience in a high-quality early care and education environment enhance the development of his or her emergent literacy? The present study is an investigation of the individual and environmental factors relevant to children’s emergent literacy skills as they unfold in time. Using a combination of principal components analysis, growth modeling with a multi-level approach, and propensity score analysis, the trajectories of growth in emergent literacy were examined. In addition to child characteristics, the effects of early child environments on emergent literacy were also examined. The effects of home literacy environment and of high-quality early care and education environments were investigated using propensity score matching techniques. The growth in emergent literacy was examined using a nationally representative dataset, the Early Childhood Longitudinal Study – Birth cohort (ECLS-B). Child characteristics, such as primary home language and poverty, were associated with lower initial abilities and suppressed growth in emergent literacy. A high-quality home literacy environment had a strong effect on the growth of children’s emergent abilities, even after controlling for child characteristics. High-quality early care and education environments, as defined by structural attributes of the program such as class size, had a modest impact on the growth of emergent literacy skills for some but not all children. When high-quality early education was defined in terms of teacher interaction, children who are exposed to such care experienced an increase in growth of their emergent literacy abilities. This study provides an examination of individual and group paths toward literacy as an element of school readiness, including the role of environment in the development of literacy skills. These findings have implications for early education policy, especially relevant to state-funded preschool programs and Early Head Start, to provide insight into contexts in which policy and the investment of resources can contribute most effectively to early literacy development.

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