李晓煦. / Submitted: Jan. 2010. / Thesis (doctoral)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (p. 170-175). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in Chinese and English. / Li Xiaoxu.

Lam, Kwok Hap. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 68-72). / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Two-level NSEM with outcomes from Exponential Family --- p.6 / Chapter 2.1 --- Basic Model Description --- p.7 / Chapter 2.2 --- Generalization from Normal Distribution to Exponential Family Distributions --- p.9 / Chapter 2.3 --- Bayesian Analysis of the Model --- p.10 / Chapter 2.3.1 --- Posterior Analysis and Gibbs Sampler --- p.10 / Chapter 2.3.2 --- Prior Distributions --- p.11 / Chapter 2.3.3 --- Bayesian Estimation --- p.13 / Chapter 2.3.4 --- Bayesian Model Selection --- p.14 / Chapter 2.4 --- A Simulation Study --- p.15 / Chapter 3 --- Two-level NSEM with mixed continuous and ordered categorical data --- p.28 / Chapter 3.1 --- Model Description --- p.29 / Chapter 3.2 --- Bayesian Analysis of the Model --- p.30 / Chapter 3.2.1 --- Posterior Analysis and Gibbs Sampler --- p.30 / Chapter 3.2.2 --- Bayesian Estimation --- p.31 / Chapter 3.3 --- A Simulation Study --- p.31 / Chapter 4 --- "Two-level NSEM with mixed continuous, count and binomial data" --- p.36 / Chapter 4.1 --- Model Description --- p.37 / Chapter 4.2 --- Bayesian Estimation --- p.38 / Chapter 4.3 --- A Simulation Study --- p.39 / Chapter 5 --- Two-level NSEM with mixed continuous and unordered categorical data --- p.43 / Chapter 5.1 --- Basic Model Description --- p.44 / Chapter 5.2 --- Bayesian Analysis of the Model --- p.47 / Chapter 5.2.1 --- Posterior Analysis and Gibbs Sampler --- p.47 / Chapter 5.2.2 --- Prior Distributions --- p.48 / Chapter 5.3 --- A Simulation Study --- p.49 / Chapter 6 --- Conclusion and Discussion --- p.53 / Chapter A --- Technical Details for Chapter 2 --- p.56 / Chapter A.1 --- Full conditional distributions --- p.56 / Chapter A.2 --- Implementation of the Metropolis-Hastings (MH) Algorithm --- p.59 / Chapter A.3 --- Gelman-Rubin statistic --- p.61 / Chapter B --- Technical Details for Chapter 3 --- p.63 / Chapter B.1 --- Full conditional distributions --- p.63 / Chapter B.2 --- Implementation of the Metropolis-Hastings (MH) Algorithm --- p.64 / Chapter C --- Technical Details for Chapter 5 --- p.66 / Chapter C.l --- Full conditional distributions --- p.66 / Bibliography --- p.68

Wang, Chang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 139-145). / Abstracts in English and Chinese. / ABSTRACT --- p.3 / CHINESE ABSTRACT --- p.5 / ACKNOWLEDGMENTS --- p.6 / TABLE OF CONTENTS --- p.7 / LIST OF TABLES --- p.9 / LIST OF FIGURES --- p.10 / INTRODUCTION --- p.11 / Chapter 1.1 --- ISSUE OF MODEL FIT IN SEM --- p.11 / Chapter 1.2 --- CLASSIFICATION AND DEVELOPMENT OF FIT INDICES --- p.13 / Chapter 1.3 --- ORGANIZATION OF THIS THESIS --- p.18 / Chapter CHAPTER 2 --- ISSUES OF FIT INDICES IN ASSESSING MODEL FIT --- p.19 / Chapter 2.1 --- SENSITIVITY OF FIS TO MODL PARAMETER --- p.19 / Chapter 2.1.1 --- Sample size --- p.20 / Chapter 2.1.2 --- Model complexity --- p.21 / Chapter 2.1.3 --- Misspecification --- p.23 / Chapter 2.2 --- MEASUREMENT ERROR --- p.26 / Chapter 2.3 --- PERFECT FIT VS. APPROXIMATE FIT --- p.26 / Chapter 2.4 --- Minimum Fit Function chi-square vs. Normal-theory Weighted Least chi-square --- p.29 / Chapter 2.5 --- RULE OF THUMB --- p.30 / Chapter 2.6 --- FIVE RESEARCH QUESTIONS --- p.37 / Chapter CHAPTER 3 --- SIMULATION --- p.39 / Chapter 3.1 --- FIT INDICES --- p.39 / Chapter 3.2 --- DESIGN OF MONTE CARLO SIMULATIONS --- p.38 / Chapter 3.3 --- MODEL COMPLEXITY AND MODEL SPECIFICATION --- p.39 / Chapter 3.4 --- SIMULATION PROCEDURE --- p.41 / Chapter CHAPTER 4 --- RESULTS --- p.45 / Chapter 4.1 --- MEASUREMENT ERROR AND CRONBACH´ةS ALPHA --- p.45 / Chapter 4.2 --- ANSWER TO Q1 --- p.45 / Chapter 4.3 --- ANSWER TO Q2 --- p.53 / Chapter 4.4 --- ANSWER TO Q3 --- p.56 / Chapter 4.5 --- ANSWER TO Q4 --- p.60 / Chapter 4.6 --- ANSWER TO Q5 --- p.62 / Chapter CHAPTER 5 --- DUSCUSSION --- p.77 / Chapter 5.1 --- DUSCUSSION TO Q1 --- p.77 / Chapter 5.2 --- DUSCUSSION TO Q2 --- p.83 / Chapter 5.3 --- DUSCUSSION TO Q3 --- p.85 / Chapter 5.4 --- DUSCUSSION TO Q4 --- p.88 / Chapter 5.5 --- DUSCUSSION TO Q5 --- p.89 / Chapter CHAPTER 6 --- LIMITATION --- p.99 / Chapter CHAPTER 7 --- CONCLUSION --- p.101 / PREFERENCE --- p.139

Pan, Junhao. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 121-135). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

O ambiente competitivo e globalização vem provocando mudanças nas estratégias das empresas, fomentando, muitas vezes, para um processo de internacionalização. As empresas procuram internacionalizar-se de acordo com seus objetivos estratégicos, traçando uma estratégia de internacionalização. Sair do seu ambiente para um país desconhecido significa que a empresa estará sujeita a correr certos riscos e, portanto, requer uma estratégia que avalie os riscos envolvidos para se estabelecer em um determinado país. O conhecimento desses riscos vai proporcionar a empresa mitigar ou mesmo eliminar os riscos envolvidos. Independente do processo de entrada em outro país, sempre haverá a questão do risco. Geralmente, quando uma empresa decide se internacionalizar, ela opta primeiro pelo processo de exportação, em que terá de lidar com vários tipos de risco em suas decisões gerenciais para alcançar seus objetivos estratégicos. Portanto, essa pesquisa foi feita com oitenta e quatro empresas exportadoras brasileiras, do estado de São Paulo, com faturamento de até 10 milhões de dólares listadas na Confederação Nacional da Indústria (CNI). O objetivo desse estudo foi entender como e quais riscos envolvidos na internacionalização de empresas exportadoras brasileiras exercem influência sobre a estratégia e objetivos estratégicos na internacionalização de empresas exportadoras. Para a análise da pesquisa, foi utilizada a técnica de modelagem de equações estruturais baseada em variância, na qual foi utilizada uma survey para coleta de dados. Foram geradas quatro hipóteses, três relacionadas ao risco e estratégia e uma relacionada à estratégia e ao risco. Como resultado, duas hipóteses foram confirmadas e, portanto, duas rejeitadas. Essa pesquisa contribui com o conhecimento científico, pois, além de verificar os riscos que influenciam na estratégia e objetivos estratégicos, ela traz a concepção de envolver riscos não somente financeiros, mas também do ambiente, do setor e da empresa na estratégia para a internacionalização. / The competitive environment and globalization has been provoking changes in the strategies of companies, often leading to an internationalization process. The companies seek to internationalize themselves according to their strategic objectives, to which a strategy of internationalization will be traced. Leaving your environment to an unknown country means that the company is subject to certain risks and therefore requires a strategy that assesses the risks involved in establishing itself in a particular country. Knowing these risks will enable the company to mitigate or even eliminate the risks involved. Regardless of the process of entry into another country, there will always be the issue of risk. Usually, when a company decides to internationalize, it opts for the first time through the export process, where it will have to deal with various types of risk in its managerial decisions to reach its strategic objectives. Therefore, this research was conducted with eighty-four Brazilian companies in the state of São Paulo, with sales of up to 10 million dollars listed in Confederação Nacional da Indústria (CNI). The objective of the study was to understand how and what risks involved in the internationalization of Brazilian exporting companies influence the strategy and the strategic objectives in the internationalization of exporting companies. But even this process depending on the intensity of export the company will be subject to risk because it is unknown to the host country. Therefore, this research was carried out with Brazilian export companies, whose objective was to investigate the influence of the risks involved in the internationalization of Brazilian exporting companies on the strategy of internationalization and strategic objectives. For the analysis of the research was used the technique of modeling of structural equations based on variance, where a survey was used to collect data. Four hypotheses were generated, three related to risk and strategy and one related to strategy and risk. As a result, two hypotheses were confirmed and therefore two rejected. This research contributes with scientific knowledge, because in addition to verifying the risks that influence the strategy and strategic objectives, it brings the concept of involving not only financial risks but also the risk of the environment, sector and the company in the strategy for internationalization.

Structural Equations Models (SEMs) are now widely used almost in every discipline of research. Most of the existing materials for the Namibian macroeconomic models are studies of the well documented time series approach. In this study, we provided a statistical approach on modelling the Namibian macroeconomics for the real and fiscal economic sectors using SEMs. The approach is based on testing the theoretical specification laid down by the Namibian Macroeconometrics Model (NAMEX) of 2004. The economic structure and relationships among the variables is evaluated by means of exploratory and confirmatory analysis and the results are congruent to the existing theory in terms of loading patterns. Between Maximum Likelihood (ML) and Generalized Least Square (GLS) estimation methods, we compared the discrepancy of parameter estimates under the commonly encountered problems of sample size, violation of underlying assumptions in the data as well as model misspecifications. GLS estimation methods seem to provide better goodness of fit indices under those conditions. We have also shown that the fiscal sector is not well represented by our SEM. We recommend further studies to employ sufficiently larger samples so that models are correctly specified.

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Learner engagement, or the involvement of the student's cognitive and emotional energy to accomplish a learning task, has been called "the holy grail of learning" (Sinatra, Heddy, & Lombardi, 2015, p. 1) because of its correlations to academic achievement, persistence, and satisfaction. In the 21st century, learning will be increasingly "blended," combining face-to-face with computer-mediated instruction. Research is already exploring learner engagement in blended contexts, but no theoretical framework guides inquiry or practice. Developing models and measures of the factors that facilitate learner engagement is important to the advancement of the domain. This multiple-article format dissertation addresses the theoretical gap in research on learner engagement in blended settings. The first article reviews the existing literature on learner engagement, delineates a set of constructs most relevant to the contexts of blended learning, and proposes a theoretical framework for learner engagement in blended settings. The second article operationalizes and tests the proposed model of blended learning engagement using exploratory and confirmatory factor analysis. It creates and evaluates an end-of-course self-report measure of cognitive and emotional engagement. The unique factor structure of online and face-to-face indicators of learner engagement is clearly demonstrated in the results of this study.

The present study tested the interactive model of affect, motivation, and engagement (Linnenbrink, 2007) in mathematics education with a nationally representative sample. Self-efficacy, self-concept, and anxiety were indicators of pleasant and unpleasant affect. Intrinsic and extrinsic motivation were indicators of mastery and performance approach. Persistence and cognitive activation were indicators of behavioral and cognitive engagement. The 2012 Programme for International Student Assessment (PISA) supplied a sample of 4,978 students from the United States for structural equation modeling. The results indicated that PISA data overall supported the interactive model. Specifically, PISA data completely supported the specification of the relationship between motivation and affect, largely supported the specification of the relationship between affect and engagement, but failed to support the specification of the relationship between motivation and engagement. Finally, PISA data largely supported the specification of the mediation effects of affect on the relationship between motivation and engagement.

Substance abuse is a serious issue in both modern and traditional societies. Besides health complications such as depression, cancer and HIV, social complications such as loss of concentration, loss of job, and legal problems are among the numerous hazards substance use disorder imposes on societies. Understanding the causes of substance abuse and preventing its negative effects continues to be the focus of much research. Substance use behaviors, symptoms and signs are usually measured in form of ordinal data, which are often modeled under threshold models in Structural Equation Modeling (SEM). In this dissertation, we have developed a general nonlinear optimizer for the software package OpenMx, which is a SEM package in widespread use in the fields of psychology and genetics. The optimizer solves nonlinearly constrained optimization problems using a Sequential Quadratic Programming (SQP) algorithm. We have tested the performance of our optimizer on ordinal data and compared the results with two other optimizers (implementing SQP algorithm) available in the OpenMx package. While all three optimizers reach the same minimum, our new optimizer is faster than the other two. We then applied OpenMx with our optimization engine to a very large population-based drug abuse dataset, collected in Sweden from over one million pairs, to investigate the effects of genetic and environmental factors on liability to drug use. Finally, we investigated the reasons behind better performance of our optimizer by profiling all three optimizers as well as analyzing their memory consumption. We found that objective function evaluation is the most expensive task for all three optimizers, and that our optimizer needs fewer number of calls to this function to find the minimum. In terms of memory consumption, the optimizers use the same amount of memory.