With its widespread use across the country and increasing evidence of its effectiveness, the wraparound process has been accepted widely as a feasible alternative to restrictive residential treatments for children with severe emotional and behavioral disorders. Yet wraparound has been implemented and conceptualized in such a variety of ways that many have begun to question whether it truly is a single definable approach. Recently, a conceptual model for wraparound was offered that included ten essential elements as the key ingredients for this approach. Subsequently, the Wraparound Fidelity Index (WFI) was designed to measure the degree to which an intervention adheres to these ten elements. The purpose of the current study was to use data collected via the WFI to provide the first empirical test of wraparound’s conceptual model. Programs providing wraparound to children with severe emotional and behavioral disorders and their families used the WFI to collect data from caregivers (n = 481), youths (n = 355; 11 to 19 years), and resource facilitators (n = 610). Confirmatory factor analysis (CFA) was used to test the fit of a series of structural models consistent with the proposed element model of wraparound. First, CFA models were examined separately for each of the elements. Second, CFA models that represent the full wraparound model were tested, separately for each of the three informants. And third, a multitrait-multimethod (MTMM) analysis was conducted using a final CFA model including all elements (traits) and the three informants (methods). Findings supported the majority of elements and WFI items when tested separately at the first step. However, at the second step, only the youth model provided adequate fit to the data. Significant modification was necessary to yield admissible solutions for the caregiver and resource facilitator models. Finally, an inadmissible solution resulted when the three informants and revised model were tested in step three. Implications of the findings for the wraparound process, the WFI, and future research are discussed.

by Wai-kwan Fong. / Bibliography: leaves 37-39 / Thesis (M.Phil.) -- Chinese University of Hong Kong, 1983

Digitized by Kansas Correctional Industries

Duan, Xin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 36-43). / Abstracts in English and Chinese. / Abstract --- p.i-ii / Acknowledgement --- p.iii / Table of Contents --- p.iv / Chapter Chapter 1 --- Introduction --- p.1 / Chapter Chapter 2 --- Related Literature --- p.6 / Chapter 2.1 --- Exchange Market Pressure Index --- p.6 / Chapter 2.2 --- The Sentiment Index --- p.11 / Chapter Chapter 3 --- Stock market sentiment --- p.16 / Chapter 3.1 --- Data --- p.16 / Chapter 3.2 --- Methodology --- p.23 / Chapter 3.3 --- Estimated Results --- p.25 / Chapter Chapter 4 --- Application to the Hong Kong stock market --- p.28 / Chapter 4.1 --- Threshold Model Estimation --- p.28 / Chapter 4.2 --- Trading Strategy --- p.30 / Chapter Chapter 5 --- Conclusion --- p.32 / Appendix: Principle Component --- p.34 / References --- p.36

Every year 33,000 women die of cervical cancer in Latin American and the Caribbean. Cervical cancer has been the leading cause of potential years of life lost in Chile. Identifying factors that increase Pap test adherence will be extremely useful for developing interventions to increase the use of the Pap test and to reduce the prevalence of cervical cancer. The purpose of this study was to develop and validate a questionnaire to examine women's beliefs about cervical cancer and the Pap test in Chilean women. The questionnaire, developed following the guidelines by Robert de Vellis, is based on the Health Belief Model. The content validity index was 0.93 after 10 Chilean expert's review. A cross-sectional design was implemented to validate the questionnaire. The sample included 333 women recruited from a women's health care center in Santiago, Chile. Exploratory factor analysis was used to evaluate validity and coefficient alpha to evaluate reliability. After six models were computed, the questionnaire was reduced from 53 to 28 items. The new questionnaire,"CPC-28" includes six domains: the barriers domain to take a Pap test considers problems related with a health care center, lack of knowledge and time, being afraid, and embarrassment; the cues to action domain considers cues from family, the health care professional, friend and media; the severity domain considers cervical cancer as a serious problem, the possibility to have a hysterectomy, radiation and chemotherapy, and to die from this disease; the susceptibility domain to take a Pap test considers symptoms, having children, and intercourse; the susceptibility to cervical cancer domain considers the risk to have the disease, age, and possibility to die; and the benefit domain includes to save a life, feel good, and to take care of health. An unexpected salient factor "need to have a Pap test" was found as part of the susceptibility domain. This finding is an important topic for future research. The CPC-28 questionnaire explained 49% of the total variance, and the reliability was .735. It was concluded that the CPC-28 questionnaire will have important implications on research, educative, and administrative role of nursing.

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Summary Taiwan is an island country. Its economic structure highly relies on the economy of the foreign trade demand. The goods of foreign trade mainly are transported by the sea. So the development of the ports has a great impact on the competitiveness of the entire country. With the trend of containerization and shipping maximization in the international ocean shipping market in recent years, every harbor faces competitions among domestic ports and challenges from neighboring foreign ports at the same time. Although the superior geographical location and the wonderful natural condition of Kaohsiung Port once made Kaohsiung the third largest container harbor in the world, it faces severe competitions from Asian-Pacific ports and the new ports in Mainland China, which have emerged in recent years. What¡¦s worse, because of the effect of the overall domestic economy and industrial structure, the ranking of Kaohsiung Port has been on the downgrade continuously: ranked eighth in the world in 2007 and would be possibly even worse as predicted. Facing the above-mentioned enormous impact, Kaohsiung Port should consider and seek a solution urgently. So this research attempts to analyze the factors of the changes in the volume of goods being transported in Kaohsiung Port, and then frame a strategy for developing the port. The main content in the study includes discussions from three levels: internal condition, external environment condition and regional factors of the port, and the analysis focuses on four aspects: development, structure, efficiency and globalization. The findings of the study are: the factors resulting in the change in the volume of goods in Kaohsiung Port include the overall economic factors, the container quantity of the transit, the emergence of the continent ports, economic and trade environment, and industrial structure. The strategy for development proposed in this research include to improve the overall economic and trade environment, to boost the increase of the transit containers, to better the facilities of the port and the efficiency of work, to increase incomes from operation and accelerate development of the area, to put emphasis on the linking among ports, global investment and management, to get rid of the excessive attention to world ranking, to advance value added and to plan for port transformation. In addition, the result of study also shows that since the port entered the fourth generation, relying mainly on containerized transport in 1990, Kaohsiung Port has been transformed slowly with the influence of international economic cultural changes. Now the harbor no longer only emphasizes on transportation but also multi-development, which pays attention to the functions of information management and knowledge economy, so the fifth generation of the port is evolving progressively.

Thesis (Ph.D.)--York University, 2008. Graduate Programme in Psychology. / Typescript. Includes bibliographical references (leaves 161-177). 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:NR39022

Spearman’s law of diminishing returns (SLODR) posits that at higher levels of general cognitive ability, the general factor (g) performs less well in explaining individual differences in cognitive test performance. The present study used factor mixture modeling to investigate SLODR in the Kaufman Assessment Battery for Children--Second Edition (KABC-II). Factor mixture modeling was a useful method to study SLODR because group membership was determined based on probabilities derived from the model. A second-order confirmatory factor model, consistent with three-stratum theory (Carroll, 1993), was modeled as a within-class factor structure. The fit of several models with varying number of classes and factorial invariance restrictions were compared. A sex covariate was also included with the models that provided the best fit for the data. The results indicated that a two-class model, which allowed for g mean differences, and class-specific g variances and subtest residual variances, provided the most parsimonious explanation of the data. Consistent with SLODR, the second-order general factor explained less subtest variance and less variance in the first-order factors for those of higher general ability. The standardized subtest residual variances were also larger in the high ability class than in the low ability class. Controlling for g, boys performed higher than girls in visual-spatial ability in each of the low and high ability classes. The findings from this study have implications for future research on the interpretation of intelligence test scores across the ability distribution. / text

Advancements in microelectronic devices and computational and storage technologies enable the collection of high volume, high speed and high dimension data in many applications. Due to the high dimensionality of these measurements, exact dependence of the observations on the various parameters or variables may not be exactly known. Factor analysis (FA) is a useful multivariate technique to exploit the redundancies among observations and reveal their dependence to some latent variables called factors. Some major issues of the conventional FA are high arithmetic complexity for real-time online implementation, assumption of static system parameters, the demand of interval forecasting, robustness against outlying observations and model selection in problems with high dimension but low number of samples (HDLS). This thesis addresses these issues and proposes new extensions to the existing FA algorithms. First, in order to reduce the arithmetic complexity, we propose new recursive FA algorithms (RFA) that recursively compute only the dominant Principal Components (PCs) and eigenvalues in the major subspace tracked by efficient subspace tracking algorithms. Specifically, two new approaches are proposed for updating the PCs and eigenvalues in the classical fault detection problem with different tradeoff between accuracy and arithmetic complexity, namely rank-1 modification and deflation. They significantly reduce the online arithmetic complexity and allow the adaption to time-varying system parameters. Second, we extend the RFA algorithm to forecasting of time series and propose a new recursive dynamic factor analysis (RDFA) algorithm for electricity price forecasting. While the PCs are recursively tracked by the subspace algorithm, a random walk or a state dynamical model can be incorporated to describe the latest state of the time-varying auto-regressive (AR) model built from the factors. This formulation can be solved by the celebrated Kalman filter (KF), which in turn allows future values to be forecasted with estimated confidence intervals. Third, we propose new robust covariance and outlier detection criteria to improve the robustness of the proposed RFA and RDFA algorithms against outlying observations based on the concept of robust M-estimation. Experimental results show that the proposed methods can effectively suppress the adverse contributions of the outliers on the factors and PCs. Finally, in order to improve the consistency of model selection and facilitate the estimation of p-values in HDLS problems, we propose a new automatic model selection method based on ridge partial least squares and recursive feature elimination. Furthermore, a novel performance criterion is proposed for ranking variables according to their consistency of being chosen in different perturbation of the samples. Using this criterion, the associated p-values can be estimated under the HDLS setting. Experimental results using real gene cancer microarray datasets show that improved prognosis can be obtained by the proposed approach as compared with conventional techniques. Furthermore, to quantify their statistical significance, the p-value of the identified genes are estimated and functional analysis of the significant genes found in the diffused large B-cell lymphoma (DLBCL) gene microarray data is performed to validate the findings. While we focus in a few engineering problems, these algorithms are also applicable to other related applications. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy