This thesis is dedicated to a comprehensive study of static series synchronous compensator (SSSC) systems utilizing cascaded-multilevel converters (CMCs). Among flexible AC transmission system (FACTS) controllers, the SSSC has shown feasibility in terms of cost-effectiveness in a wide range of problem-solving abilities from transmission to distribution levels. Referring to the literature reviews, the CMC with separated DC capacitors is clearly the most feasible topology for use as a power converter in the SSSC applications. The control for the CMC-Based SSSC is complicated. The design of the complicated control strategy was begun with well-defined system transfer functions. The stability of the system was achieved by trial and error processes, which were time-consuming and ineffective. The goal of this thesis is to achieve a reliable controller design for the CMC-based SSSC. Major contributions are addressed as follows: 1) accurate models of the CMC for reactive power compensations in both ABC and DQ0 coordinates, and 2) an effective decoupling power control technique. To simplify the control system design, well-defined models of the CMC-Based SSSC in both ABC and DQ0 coordinates are proposed. The proposed models are for the CMC-Based SSSC focus on only three voltage levels but can be expanded for any number of voltage levels. The key system transfer functions are derived and used in the controller design process. To achieve independent power control capability, the control technique, called the decoupling power control used in the design for the CMC-Based STATCOM is applied. This control technique allows both the real and reactive power components to be independently controlled. With the combination of the decoupling power control and the cascaded PWM, a CMC with any number of voltage levels can be simply modeled as a three-level cascaded converter, which is the simplest topology to deal with. This thesis focuses on the detailed design process needed for a CMC-Based SSSC. / Master of Science

In this report, I study familial longitudinal count data with a Poisson regression model. The data is collected from individuals who are nested in families. I focus on two main issues to fit a model. The first one is the large number of excess zeros and the second one is multi-level random effects. My approach for solving these problems are to use either Zero Inflated Poisson (ZIP) or Negative Binomial (NB) models to control for the excess zeros which allow for estimation of another parameter for over dispersion while developing the model with individual and familial random effects. First, I use a Poisson regression model with only main effects. After that, I fit a ZIP model to control for the extra zeros. I provide information about general form of the exponential families and a discussion about the dispersion parameter. I also fit a Negative Binomial model instead of the ZIP model. I also build these models with only individual random effects and with both individual and familial random effects as well. I discuss the generalized estimating equation (GEE) approach to estimate the parameters of a generalized linear model with auto regressive correlation between outcomes. / text

The current study proposed a new model, termed the cross-classified multiple membership latent variable regression (CCMM-LVR) model, to be utilized for multiple membership data structures (for example, in the presence of student mobility across schools) that provides an extension to the three-level latent variable regression model (HM3-LVR). The HM3-LVR model is beneficial for testing more flexible, directional hypotheses about growth trajectory parameters and handles pure clustering of participants within higher-level units. However, the HM3-LVR model involves the assumption that students remain in the same cluster (school) throughout the duration of the time period of interest. The CCMM-LVR model, on the other hand, appropriately models the participants’ changing clusters over time. The first purpose of this study was to demonstrate use and interpretation of the CCMM-LVR model and its parameters with a large-scale longitudinal dataset that had a multiple membership data structure (i.e., student mobility). The impact of ignoring mobility in the real data was investigated by comparing parameter estimates, standard error estimates, and model fit indices for the two estimating models (CCMM-LVR and HM3-LVR). The second purpose of the dissertation was to conduct a simulation study to try to understand the source of potential differences between the two estimating models and find out which model’s estimates were closer to the truth given the conditions investigated. The manipulated conditions in the simulation study included the mobility rate, number of clustering units, number of individuals (i.e., students) per cluster (here, school), and number of measurement occasions per individual. The outcomes investigated in the simulation study included relative parameter bias, relative standard error bias, root mean square error, and coverage rates of the 95% credible intervals. Substantial bias was found across conditions for both models, but the CCMM-LVR model resulted in the least amount of relative parameter bias and more efficient estimates of the parameters, especially for larger numbers of clustering units. The results of the real data and simulation studies are discussed, along with the implications for applied researchers for when to consider using the CCMM-LVR model versus the misspecified HM3-LVR model. / text

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Keywords: General transformation model, Model Misspecification, Marginal likelihood, Markov chain Monte Carlo, Stochastic approximation, Mixed-effects model, Consistency, Asymptotic normality, Discretization technique. / Part II of this thesis concerns studies of mixed-effects general transformation models, i.e. general transformation models incorporating both fixed and random effects, to analyze grouped or clustered data. Rank-based marginal likelihood estimation is proposed. The estimation procedure is baseline-free, a good property enjoyed by the Cox partial likelihood. A three-stage Markov chain Monte Carlo stochastic approximation (MCMC-SA) algorithm is developed to find the maximum marginal likelihood estimation (MMLE). The asymptotic normality is obtained via a discretization procedure. Monte Carlo simulation shows that the MMLE has a good small- and moderate-sample behavior. In the end we illustrate an application of the proposed method to Hong Kong horse racing data. / Since it was first proposed by Dabrowska and Doksum in 1988, there is an explosive growth in both studies and applications of transformation model. Transformation model has many naturally endowed merits such as flexibility and conciseness in modeling lifetime or duration and ranking data involving covariates. However, like many other statistical models, transformation model may suffer the problem of misspecification due to falsely specified error term distribution or omitted covariates. The author investigates the large sample behavior of the rank-based quasi maximum marginal likelihood estimator (QMMLE) when transformation model is misspecified, and shows that owing to model misspecification, the QMMLE converges not to the true value of the parameter of interest, but to a "pseudo-true value" which minimizes the Kullback-Leibler divergence between the true model and the misspecified working model. A robust "sandwich" estimate of variance is proposed. The asymptotic normality of the QMMLE is also proved. Following the steps of White (1982), the appropriate Wald test statistic, Lagrange Multiplier test statistic and Information matrix specification test statistic are proposed. / Ni, Zhongxin. / Adviser: Ming Gao Gu. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3587. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 86-99). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Since 1949 Taiwan and China have been governed by different political regimes. Nevertheless, after more than fifty years, research shows that women in both societies now enjoy significantly higher social status and have lower fertility rates. Despite well-documented literature on the relationship between fertility and women??s status in Taiwan and China, no systematic empirical research has compared the two. This dissertation was designed to investigate the effects of women??s status on fertility and sterilization behaviors in China and Taiwan by means of multi-level analysis focusing on women??s education levels and employment status as predictors at both the individual and aggregate levels. To examine the influence of enforced policy, in China??s models, variables were added about whether the participants had a government-issued one-child certificate or had complied with the childbirth quota set by local authorities. Most results are consistent with our hypotheses. At the macro level, female college graduation rate is significant in Taiwan but not in China. One-child certificate rate is significantly correlated with provincial-level number of Child Ever Born (CEB). At the micro level of Poisson and logistic models, women with status are significantly more likely to have smaller numbers of CEB and lower sterilization usage. Survival analysis that simultaneously analyzed time duration and event occurrence showed dynamic effects of women??s status on the probability of a first, second and third childbirth. The Hierarchical Generalized Linear Models (HGLM) method shows both some direct and some interactive effects of contextual variables on fertility and contraceptive behaviors. In both countries, wives?? educational levels showed the greatest numbers of significant correlations with the dependent variables. Both Western socioeconomically based demographic transition theory and Asian planned demographic transition theory in China receive empirical support in the findings. Methodological and policy implications for future studies are discussed. The findings of this dissertation, particularly the micro-macro linkages, contribute to an explanation of how higher women??s status and lower fertility rates across the two regimes emerged from both common and disparate processes. This dissertation also illustrates how multi-level investigations of fertility and women??s status could be implemented in other parts of the world.

In this report we give a brief introduction to the multilevel models, provide a brief summary of the need for using the multilevel model, discuss the assumptions underlying use of multilevel models, and present by means of example the necessary steps involved in model building. This introduction is followed by a discussion of power and sample size determination in multilevel designs. Some formulae are discussed to provide insight into the design aspects that are most influential in terms of power and calculation of standard errors. Finally we conclude by discussing and reviewing the simulation study performed by Maas and Hox (2005) about the influence of different sample sizes at individual as well as group level on the accuracy of the estimates (regression coefficients and variances) and their standard errors. / text

The majority of research on suicide has focused on the role of direct risk factors in the development of suicidal intent, including personal characteristics and psychiatric illness. While research on the wider influence of socio-economic circumstances is not uncommon, most research has considered single risk factors, and often limits the scope of the research to small groups or small areas. This research attempted to provide a unified and comprehensive analysis, and used mainly aggregate data to consider the extent to which socio-economic factors explain geographic and temporal variations in suicide. Variations in suicide over the local authority districts of England and Wales were found to be significantly associated with several ecological predictors, including male unemployment, lone households, low social class and divorce. The importance of the predictors varied according to age and sex, and the results corresponded well to those from individual level studies. The research also considered the geographical differences between suicide and undetermined death verdicts, and found that the latter have a significant urban bias. These cross- 3ectional results were used as the basis for a study of the changes that took place in suicide rates during the 1980s, to determine the extent to which changes in the area characteristics that were significant at a given point in time accounted for changes in suicide rates over time. Particular attention was given to the dramatic rise in rates among younger males (aged 15-44). Little evidence was found at the ecological level to support the hypothesis that changes in unemployment and/or deprivation, the proportion of people living alone, or the divorce rate might have been responsible for the increase in suicide among younger men, while the rates for all other groups declined. Individual data for Norfolk were also used, and the predictors of geographic variation were found to be very similar for Norfolk and England and Wales. Furthermore, although the sexand age-specific changes in rates during the 1980s were also similar, the ecological variable~ again failed to adequately predict the changes. Analysis did not support the hypothesis tha1 suicide rates increased solely because of the increased availability of motor vehicle exhaus1 fumes as a suicide method, though there was some suggestion that this may have contributec to the trends. Further analysis of individual deaths found strong evidence to suggest the urbar bias of undetennined death to be an artifact of the reporting of suicide, whereby mon equivocal methods, more likely to lead to an undetermined death verdict, tend to be use( more often in urban areas. Two main conclusions are reached. First, the extent of the urban-rural variation between tbl verdicts was such that studies using different definitions of suicide over the same study are; could possibly derive diifering conclusions. Combining the verdicts is therefore encouragec Second, while the geography of suicide may be explained in tenns of socio-economic facton changes in suicide rates appear to have little or no geographic and socio-economi manifestation. Detennining the role of cultural change, presently the only theory t adequately account for the divergence in rates, requires more psychologically and socially orientated research.

Thesis (M.A.)--York University, 2007. Graduate Programme in Social Anthropology. / Typescript. Includes bibliographical references (leaves 140-143). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR31974

Thesis (Ph. D.)--Georgia State University, 2008. / Title from file title page. Carolyn F. Furlow, committee chair; Phillip Gagne, T. Chris Oshima, Christopher Domaleski, committee members. Electronic text (113 p.) : digital, PDF file. Description based on contents viewed June 24, 2008. Includes bibliographical references (p. 96-101).