Dissertations / Theses on the topic 'Bioproducts; Structural change; Models'
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Chen, Ya-Huei. "A study of freeze denaturation of proteins." Thesis, University of Oxford, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365813.
Full textWestin, Lars. "Vintage models of spatial structural change." Doctoral thesis, Umeå universitet, Institutionen för nationalekonomi, 1990. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-73665.
Full textdigitalisering@umu
Zeileis, Achim, Friedrich Leisch, Christian Kleiber, and Kurt Hornik. "Monitoring structural change in dynamic econometric models." SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, 2002. http://epub.wu.ac.at/1296/1/document.pdf.
Full textSeries: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
Zeileis, Achim, and Christian Kleiber. "Validating multiple structural change models. A case study." Institut für Statistik und Mathematik, WU Vienna University of Economics and Business, 2004. http://epub.wu.ac.at/584/1/document.pdf.
Full textSeries: Research Report Series / Department of Statistics and Mathematics
Barth, Volker. "Integrated assessment of climate change using structural dynamic models." Hamburg : Max-Planck-Inst. für Meteorologie, 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=968535933.
Full textZeileis, Achim, and Christian Kleiber. "Validating multiple structural change models. An extended case study." Institut für Statistik und Mathematik, WU Vienna University of Economics and Business, 2005. http://epub.wu.ac.at/280/1/document.pdf.
Full textSeries: Research Report Series / Department of Statistics and Mathematics
Zheng, Pingping. "Bayesian analysis of structural change in trend." Thesis, Nottingham Trent University, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.391001.
Full textFröberg, Malvina. "Testing for Structural Change in Regression Models of Meat Consumption in Sweden." Thesis, Uppsala universitet, Tillämpad matematik och statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-318686.
Full textAzam, Mohammad Nurul 1957. "Modelling and forecasting in the presence of structural change in the linear regression model." Monash University, Dept. of Econometrics and Business Statistics, 2001. http://arrow.monash.edu.au/hdl/1959.1/9152.
Full text黃少軍 and Shaojun Huang. "Service sector development, structural change, and economic growth: international experriences and implicationsfor China." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31241815.
Full textZeileis, Achim, Friedrich Leisch, Kurt Hornik, and Christian Kleiber. "strucchange. An R package for testing for structural change in linear regression models." SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, 2001. http://epub.wu.ac.at/1124/1/document.pdf.
Full textSeries: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
Kleiber, Christian, Kurt Hornik, Friedrich Leisch, and Achim Zeileis. "strucchange: An R Package for Testing for Structural Change in Linear Regression Models." American Statistical Association, 2002. http://epub.wu.ac.at/4001/1/strucchange.pdf.
Full textPereira, Manuel Bernardo Videira Coutinho Rodrigues. "Effects of fiscal policy: measurement issues and structural change." Doctoral thesis, Instituto Superior de Economia e Gestão, 2011. http://hdl.handle.net/10400.5/3431.
Full textConsiderable uncertainty surrounds the macroeconomic effects of fiscal policy. The re-search presented in this dissertation firstly aims at improving on the methods used to measure such effects - which feature vector autoregressions (VARs) as the basic tool. The investigation is partly carried out using structural VARs. The methodological innova¬tions in that part concern the joint identification of fiscal shocks vis-a-vis monetary policy shocks and the estimation of a model with time-varying parameters using a non-recursive identification scheme. I also use reduced-form VARs to assess the effects of a novel shock measure, derived from budget forecasts, that is arguably free of anticipatory movements. The second aim of the dissertation is to present empirical results for the US, focusing on the way the impacts of the government budget on the economy have changed over time. The thesis is divided into three essays. In the first one, I present evidence that taxes and transfers were the most important force attenuating the severity of recessions up to the eighties, surpassing the role of monetary policy. Fiscal policy has, however, become less effective in stimulating output in the course of the last decades. The findings in the second and the third essays corroborate this conclusion. Such a change in effectiveness is particularly marked for the shock measure that is relatively unaffected by anticipation, which features multipliers with non-conventional signs in the recent period. In general, these findings call for more research on the factors that intervene in the transmission mechanism of fiscal policy and can bring about important variation in its impacts.
Huang, Huilin. "Modelling structural change in the U.S. demand for meat." Thesis, Virginia Tech, 1991. http://hdl.handle.net/10919/42003.
Full textWhen modelling the demand for beef, pork, chicken and turkey, none
of the three demand systems are found to be statistically adequate, and
consequently, cannot be used to address structural change issues for
these particular data and commodities. The AIDS models are re-estimated
in an attempt to model the demand for beef, pork, chicken and fish
instead of turkey. The dynamic versions of the AIDS models using either
a gradual shift spline path, a Farley-Hinich path, a variable measuring
cholesterol awareness, or the log of the cholesterol awareness variable
are all statistically adequate. Likelihood ratio tests on these models
indicate that structural change has occurred. The significance of the
cholesterol variable in the demand models indicates that health concern
is an important factor in meat purchasing decisions.
Master of Science
Zeileis, Achim, Ajay Shah, and Ila Patnaik. "Testing, monitoring, and dating structural changes in maximum likelihood models." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2008. http://epub.wu.ac.at/1224/1/document.pdf.
Full textSeries: Research Report Series / Department of Statistics and Mathematics
Li, Fuchun. "Testing for and dating structural change in econometric models and nonparametric methods in finance." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0017/NQ58145.pdf.
Full textLama, Salomon Abraham. "Digital State Models for Infrastructure Condition Assessment and Structural Testing." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/84502.
Full textPh. D.
Barth, Volker [Verfasser]. "Integrated assessment of climate change using structural dynamic models / Max-Planck-Institut für Meteorologie. Von Volker Barth." Hamburg : Max-Planck-Inst. für Meteorologie, 2003. http://d-nb.info/968535933/34.
Full textMuhsal, Birte Chantal Simone [Verfasser]. "Change-Point Methods for Multivariate Autoregressive Models and Multiple Structural Breaks in the Mean / Birte Chantal Simone Muhsal." Karlsruhe : KIT-Bibliothek, 2013. http://d-nb.info/1036681300/34.
Full textMaerten-Rivera, Jaime. "A Comparison of Modern Longitudinal Change Models with an Examination of Alternative Error Covariance Structures." Scholarly Repository, 2010. http://scholarlyrepository.miami.edu/oa_dissertations/376.
Full textVikström, Peter. "The big picture : a historical national accounts approach to growth, structural change and income distribution in Sweden 1870-1990." Doctoral thesis, Umeå universitet, Institutionen för ekonomisk historia, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-59808.
Full textdigitalisering@umu
Guillard, Charlotte. "Rethinking economic growth and structural change : the role of boundaries and linkages between industries." Thesis, Strasbourg, 2019. http://www.theses.fr/2019STRAB022.
Full textEconomic development is associated with changes in production and export structures. Each country masters a set of capabilities, i.e. a set of tasks and knowledge necessary for the realization of some products. Mastering additional capabilities allows countries to produce more complex products or technologies. Understanding economic development involves understanding how countries can add new products to their production and export basket and develop particular industries. Each industry has specific characteristics in terms of capabilities, technologies and knowledge and in terms of the nature of their production. In this thesis, I provide empirical evidence of the importance of both boundaries and linkages between industries to understand structural change and the dynamics of economic growth. Chapter 2 proposes a new methodology for identifying patterns of organization of industries and their evolution over time. To do this, I analyze the cluster structure of the product network built from export data. Results show that products cluster according to different factors: their complexity and technological domains, the abundance of low-skilled labor or of natural resources they require, as well as global value chains and vertical integration of their production process. Moreover, I find that technological domains and boundaries between industries are not always clear-cut and can evolve over time. In chapter 3, I study the dynamics of economic growth by examining the characteristics and determinants of transitions between different medium-term growth regimes (rapid growth, slow growth and recession) using a semi-Markov framework. Results indicate that the effect of the manufacturing sector on economic growth is far from uniform and that the measure of economic structure also matters. In addition, clusters with similar technological intensity play a different role in the dynamics of growth, and, global value chains (GVCs) may explain some of these differences. Furthermore, although the textile industry is often seen as a steppingstone to industrialization, in this study the effect of this cluster is negative in many cases. Finally, this analysis highlights the presence of “recession traps”, which are largely driven by a greater specialization natural resources-based manufacturing clusters. Differences between industries affect not only the growth process through productivity gaps, but also the stimulation they provide to the rest of the economy through upstream and downstream linkages. Chapter 4 examines the impact of inter-industry interconnections on economic performance,focusing on demand dynamics (i.e. backward linkages). I relax two strong assumptions associated with the traditional calculation of the output multiplier, which makes it possible to estimate the degree of response to demand shocks from the supplying industries. Results show that there are significant differences across industries and countries. Manufacturing industries, and in particular final consumer goods ones, tend to be less responsive to shocks in demand relative to services. Significant differences are also observed between countries since manufacturing industries in developed countries tend to be less sensitive to demand shocks than in developing countries
Ameen, Masood, and Mini Jacob. "Complexity in Projects : A Study of Practitioners’ Understanding of Complexity in Relation to ExistingTheoretical Models." Thesis, Umeå University, Umeå School of Business, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-18376.
Full textIn the last three decades, complexity theory has gained a lot of importance in several scientific disciplines like astronomy, geology, chemistry etc. It has slowly extended its usage in the field of project management. While trying to understand the managerial demands of modern day projects and the different situations faced in projects, the term ‘complexity’ is progressively becoming a benchmark term. In the recent past some of the challenging projects that have been completed are the Heathrow Terminal 5 and the construction of venues for the Beijing Olympics. But can we call these projects complex?It is probably too simplistic to classify projects as complex or non-complex. What is particularly important is to identify the source of the complexity, the level and also the implications of the complexity. Several academicians have studied the different dimensions and established different classifications of complexity. These are put together into models of complexity.But is this classification well-grounded in reality? This is what we aim to explore through this research. The specific questions that we wish to explore by conducting this research are:
- How does the understanding of project complexity in actuality conform to the theoretical complexity models?
In an effort to answer the primary question, our study will also throw some light on factors of complexity across different sectors. We hope that this distinction will pave way for further research within these sectors. This now brings us to our sub-question:- How do the factors that contribute to complexity compare across different sectors?At the outset of this research, the literature on complexity was reviewed. An attempt was made to understand what complexity means with a focus on the field of project management.It was observed that there is a new wave of thinking in this field and a camp which believes that regular project management tools and techniques cannot be used for complex projects.
This has drawn several academicians to generate models of complexity based on various factors. In this research we have focused on some important models like that of Turner and Cochrane, Ralph Stacey, Terry Williams, Kahane and Remington and Pollack. We have tried to see if any of these models fit in with how practitioners understand complexity.To find out how practitioners comprehend complexity, we followed a grounded theory approach and also used quantitative methods to supplement the results in accordance in a mixed methodology. Semi-structured interviews were carried out with nine project managers from different sectors and different geographical locations. The interviews were analyzed and the data was broken down to different categories referred to as open coding where labelling was done. This was followed by Axial coding where we describe the properties and build relations between these categories. The final stage is selective coding where the emerged theory is integrated and refined.Quantitative data was collected through a short questionnaire which listed out some factors which could cause or lead to complexity in projects. A total of 29 responses were obtained for the questionnaires. By analyzing this data we were able to determine the factors that project managers thought caused complexity in projects. A new dimension was also added by analyzing it sector-wise. Since we collected data from two different sources, via interviews and through questionnaires, it gave us the opportunity to triangulate the findings. Wesincerely hope that this piece of work will pave way for future research on similar areas like models of complexity and perception of complexity in project management
Eklöf, Jan A. "Varying data quality and effects in economic analysis and planning." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 1992. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-903.
Full textDiss. Stockholm : Handelshögsk.
López, Buenache Germán. "Essays on Forecasting Methods and Monetary Policy Evaluation." Doctoral thesis, Universidad de Alicante, 2015. http://hdl.handle.net/10045/50225.
Full textStuart, Graeme. "Monitoring energy performance in local authority buildings." Thesis, De Montfort University, 2011. http://hdl.handle.net/2086/4964.
Full textSaint-Cyr, Legrand Dunold Fils. "Prise en compte de l’hétérogénéité inobservée des exploitations agricoles dans la modélisation du changement structurel : illustration dans le cas de la France." Thesis, Rennes, Agrocampus Ouest, 2016. http://www.theses.fr/2016NSARE043/document.
Full textStructural change in farming has long been the subject of considerable interest among agricultural economists and policy makers. To account for heterogeneity in farmers’ behaviours, a mixture Markov modelling framework is applied to analyse this process for the first time in agricultural economics. The performance of this approach is first investigated using a restrictive form of the model, and its general form is then applied to study the impact of some drivers of structural change, including agricultural policy measures. To identify channels through which interdependency between neighbouring farms arises in this process, the mixture modelling approach is applied to analyse both farm survival and farm growth. The main conclusions of this thesis are threefoldFirstly, accounting for the generally unobserved heterogeneity in the transition process of farms allows better representing structural change in farming and leads to more accurate predictions of farm-size distributions than the models usually used so far. Secondly, the impacts of the main drivers of structural change themselves depend on the specific unobservable farm types which are revealed by the model. Lastly, the mixture modelling approach enables identifying different unobserved relationships between neighbouring farms that contributes to the structural change observed at an aggregate or regional level
Niang, Abdou-Aziz. "Croissance et convergence des pays de la zone CFA : une étude par les données de panel non stationnaires." Phd thesis, Université de Bourgogne, 2011. http://tel.archives-ouvertes.fr/tel-00834421.
Full text"Validating multiple structural change models." Institut für Statistik und Mathematik, 2004. http://epub.wu-wien.ac.at/dyn/dl/wp/epub-wu-01_708.
Full textWang, Ling-Yo, and 王怜又. "Monitoring Structural Change in Dynamic Econometric Models." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/01458344653085683106.
Full text淡江大學
財務金融學系碩士班
94
This research consider a wide array of fluctuation-type tests in a monitoring situation—given a history period for which a regression relationship is known to be stable, we test whether incoming data are consistent with the previously established relationship. We apply our methods to three data sets, returns of West Texas Intermediate oil, returns of Brent crude oil, and S&P 500 stock returns. Then, we generate simulated out-of-sample forecasts, forecast errors, and tests of mean square error (MSE) for a pair of nested models (the first model is a restricted version of the second) of a scalar prediction. The empirical results included that: (1) we can find structural changes from these three data sets by the generalized fluctuation test for monitoring. (2) the rolling forecast models of returns of WTI oil and returns of Brent crude oil both display that considering the factor of structure change will increase the power of forecast.
"Testing and estimating structural change in misspecified linear models." 1997. http://library.cuhk.edu.hk/record=b5889147.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 1997.
Includes bibliographical references (leaves 84-89).
Chapter 1 --- Acknowledgment --- p.6
Chapter I --- Introduction and a Structural Change Model --- p.7
Chapter 2 --- Introduction --- p.7
Chapter 3 --- A Structural Change Model and the Estimated Specification --- p.10
Chapter II --- Behavior of the Model under Stationarity --- p.13
Chapter 4 --- Assumptions for Stationary Regressors and Error --- p.13
Chapter 5 --- Consistency of the Break Point Estimator when Regressors and Error are Stationary and Correlated --- p.14
Chapter 6 --- Limiting Distribution of the Break Point Estimator when Regressors and Error are Stationary and Correlated --- p.19
Chapter 7 --- Sup-Wald Test when Regressors and Error are Stationary and Correlated --- p.21
Chapter III --- Behavior of the Model under Nonstationarity --- p.23
Chapter 8 --- Assumptions for Nonstationary Regressors and I(d) Error --- p.23
Chapter 9 --- Consistency of the Break Point Estimator under Nonstationary Regres- sors and I(d) Error --- p.26
Chapter 10 --- F Test under Nonstationary Regressors and I(d) Error --- p.31
Chapter IV --- Finite Sample Properties and Conclusion --- p.33
Chapter 11 --- Finite Sample Properties of the Break Point Estimator --- p.33
Chapter 12 --- Conclusion --- p.38
Chapter V --- Appendix and Reference --- p.40
Chapter 13 --- Appendix --- p.40
Chapter 14 --- References --- p.84
Liao, Shian-Yu, and 廖先昱. "Business Cycles and Structural Change: Two-Sector Growth Models." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/07634691151404896315.
Full text國立臺灣大學
經濟學研究所
102
This dissertation consists of three essays concerning structural change and business cycles in response to real and nominal shocks in multi-sector growth models. In the first essay, I study and compare the relationship between sectoral total factor productivity and economic structural transformation in different models. Several papers showed that growth in agricultural productivity was essential for today’s richest countries to take off early. However, few articles noticed that growth in agricultural productivity is critical in governing long-term and large structural changes in richest countries of today. This essay studies a two-sector neoclassical growth model with subsistence agricultural consumption and agricultural capital, and shows that (i) hold-up effect which follows on complementarity between capital and labor is crucial; and (ii) growth in agricultural productivity plays a more important role than growth in non-agricultural productivity in determining long-term and large structural changes in richest countries of today. Next, the second essay analyzes the problem of consumption dynamics between nondurables and consumer durables in response to monetary policy shocks. Empirical results indicate that consumer durables and nondurable consumption tend to comove in response to monetary policy shocks, and consumer durable prices are more flexible than nondurable prices. However, in otherwise standard two-sector neoclassical sticky-price models with flexible durable prices, following a contractionary monetary policy shock, nondurables decrease but consumer durables increase (substitution effect). Credit constraints can generate a negative income effect for borrowers because of tighter credit constraints resulted from a contractionary monetary policy. However, if durable prices are flexible, substitution effect dominates income effect, so the model still fails to generate joint decline. This essay resolves the comovement problem by adding firms’ investment and financial friction into a model with flexible durable prices. When investment is chosen by firms, contractionary monetary policy shocks reduce the relative price of durables, which induces investment and decreases firms’ real profits in the short run. Due to fewer profits remitted from firms, savers have a lower disposable income and cannot increase expenditures on consumer durables as much as otherwise. As a consequence, together with the credit constraint channel, aggregate consumer durables decrease and comove with nondurables. Finally, the third essay investigates the business cycle comovement problem driven by investment shocks. Recent research based on sticky-price models suggests that investment shocks are the most important driver of business cycle fluctuations. Yet, investment shocks generate the comovement problem because there is an intertemporal substitution effect away from consumption and toward investment, which is inconsistent with empirical evidence that consumption tends to comove along with other real macro variables procyclically. This essay resolves the comovement problem by extending the standard neoclassical sticky-price model to a two-sector model with consumer durable services. When investment goods are used for either capital investment or consumer durable services, positive investment shocks also generate an intratemporal substitution effect away from consumer durable services toward consumption. As the intratemporal substitution effect dominates the intertemporal substitution effect, consumption increases, and thus the comovement problem in business cycles is resolved.
Lee, Kai-Min, and 李凱民. "The structural change problems in regression and return prediction models." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/11730866542340009464.
Full text逢甲大學
統計與精算所
97
This paper investigates structural change problems in regression and return prediction models, it is difficult to fit those models when there exists structural changes. Here specific targets can be separated into the two parts. First, for segmented regression models, we discuss how to classify the groups in mixture data, and apply the Bayesian method and the data augmentation to estimate unknown parameters include threshold values, intercepts, piecewise slopes and latent variables. Second, for return prediction models, the stock return is affected by some state variables in certain periods to arise the structural changes problem. We consider a structural break in instability of return prediction model with heteroskedasticity and employ a Bayesian approach to identify a structural break at an unknown breakpoint in the model. We simultaneously make inference unknown parameters and a breakpoint. Finally, we carried out simulation studies and empirical examples for both models. The illustrations of simulation studies and empirical examples present the well performance of the proposed algorithms. The results display the Bayesian method is proposed which can properly simultaneously identify the changepoint and estimate unknown parameters above two models.
"Identification of structural-change models when the dummy regressor is misclassified." 2001. http://library.cuhk.edu.hk/record=b5890709.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 2001.
Includes bibliographical references (leaves 50-52).
Abstracts in English and Chinese.
ACKNOWLEDGMENT --- p.iii
CHAPTER
Chapter ONE --- INTRODUCTION AND LITERATURE REVIEW --- p.1
Chapter TWO --- THE MODEL --- p.3
Chapter THREE --- ASYMPTOTIC BEHAVIOR OF THE LEAST SQUARES ESTIMATORS --- p.6
Chapter FOUR --- EIGHT SPECIAL CASES --- p.12
Chapter FIVE --- MONTE CARLO EXPERIMENTS --- p.36
Chapter SIX --- CONCLUSION --- p.40
APPENDIX --- p.41
BIBLIOGRAPHY --- p.50
Liu, Chien-Wei, and 劉建緯. "The Comparison and Application of the ACD Models of Structural Change." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/5879gm.
Full text銘傳大學
財務金融學系碩士班
95
Several stock exchanges provide all records of trade and quote. Engle (2000) refers to these records as ultra-high-frequency data. This study employs the ultra- high-frequency data to apply a unified framework for testing and evaluating the adequacy of an estimated autoregressive conditional duration (ACD) model. The method of the test is the Lagrange multiplier test. This method can test against general forms of additive and multiplicative misspecifications of the conditional duration function, including tests against higher-order models, tests of no remaining ACD in the standardized duration. Next, this study applies the smooth transition ACD model (STACD) for tests of linearity. Finally, this study applies the time-varying ACD model (TVACD) for testing the parameter constancy. The empirical results of this study indicate that most of the trade durations of Taiwan Semiconductor Manufacturing Co. (TSMC), United Microelectronics Corp., Advanced Semiconductor Engineering Inc., and AU Optronics Corp. fit the lower order ACD models. In the aspect of price duration, when the sample periods become longer before the change of the tick size, the appropriate lag orders of the ACD models would become lower or unchanged. When the sample periods become longer after the change of the tick size, the appropriate lag orders of the ACD models would become higher, lower or unchanged. Under the sample periods of a week or a month before and after the change of the tick size, the appropriate lag orders of the ACD models would become higher, lower or unchanged. Next, we also find that the STACD model appropriately simulates the trade duration and price duration of TSMC. Finally, the empirical results reveal that the price duration of TSMC is more appropriately fitted by the TVACD model.
Kuo, Wen-Cheng, and 郭文正. "The Structural Models of the Addicts' Social Support, Stress, and Stages of Change." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/59304648220406653923.
Full text國立臺灣師範大學
教育心理與輔導學系
100
This study focused on the status quo, differences, and relationships among the addicts' severity of drug abuse, social support, stress, and stages of change. This research was based on the data collected from the 613 subjects in the Drug Abuse Treatment Centers. The researcher established exploratory an structural equation model by literatures and using statistical analysis to understand. The important findings were as follows: (1) There was significant difference between male and female in the stages of change and in the readiness of change. (2) In the stages of change and in the readiness of change, there was significant difference between the addicts who have and have not sought professional treatment. (3) There were significant correlations between the dimension of severity of drug abuse, dimension of social support, dimension of stress, and dimension of stages of change. (4) The measures and structural models of addiction severity, social support of drug abuse treatment time, stress of drug abuse treatment time, and stages of change had appropriate goodness-of-fit. In such models, social support of drug abuse treatment time had the greatest effects on the sense of losing control, social support of drug abuse treatment time had the greatest effects on stages of change. (5) The measures and structural models of addiction severity, expected social support after release, expected stress after release, and stages of change had appropriate goodness-of-fit. In such models, expected social support after release had the greatest effects on expected stress after release, addiction severity had the greatest effects on stages of change. Expected social support after release and expected stress after release had no direct effect on stage of contemplation, stage of action, and stage of maintenance. (6) The original measures and structural models of addiction severity, social support, stress, and stages of change had appropriate goodness-of-fit. Expected social support after release and expected stress after release had a direct effect on stage of precontemplation. (7) The modified measures and structural models of addiction severity, social support, stress, and stages of change had appropriate goodness-of-fit. In such models, addiction severity, social support of drug abuse treatment time and stress of drug abuse treatment time had direct effects on stages of change. Expected social support after release and expected stress after release had indirect effects on stages of change. Addiction severity had the greatest effects on stage of precontemplation. Social support of drug abuse treatment time or stress of drug abuse treatment time had the greatest effects on stage of contemplation, stage of action, stage of maintenance. Based on the findings, the researcher made the following recommendations: (1) establishing a system of assessment for understanding the drug addicts' motivation of change; (2) assisting the drug addicts in establishing a social support network and continuing it after release; (3) assisting the drug addicts in learning to cope ; (4) giving individual treatment for enhancing their motivation and ability to change.
Ma, Guangyi. "Three Essays on Estimation and Testing of Nonparametric Models." Thesis, 2012. http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11768.
Full textYang, Lili. "Joint models for longitudinal and survival data." Thesis, 2014. http://hdl.handle.net/1805/4666.
Full textEpidemiologic and clinical studies routinely collect longitudinal measures of multiple outcomes. These longitudinal outcomes can be used to establish the temporal order of relevant biological processes and their association with the onset of clinical symptoms. In the first part of this thesis, we proposed to use bivariate change point models for two longitudinal outcomes with a focus on estimating the correlation between the two change points. We adopted a Bayesian approach for parameter estimation and inference. In the second part, we considered the situation when time-to-event outcome is also collected along with multiple longitudinal biomarkers measured until the occurrence of the event or censoring. Joint models for longitudinal and time-to-event data can be used to estimate the association between the characteristics of the longitudinal measures over time and survival time. We developed a maximum-likelihood method to joint model multiple longitudinal biomarkers and a time-to-event outcome. In addition, we focused on predicting conditional survival probabilities and evaluating the predictive accuracy of multiple longitudinal biomarkers in the joint modeling framework. We assessed the performance of the proposed methods in simulation studies and applied the new methods to data sets from two cohort studies.
National Institutes of Health (NIH) Grants R01 AG019181, R24 MH080827, P30 AG10133, R01 AG09956.