Fertility patterns in European Union Abstract The main objective of the thesis is to create a typology of fertility in the countries of European Union. The variables entering the analysis are demographic indicators of fertility (total fertility rate, mean age of women at first birth) and opinion poll Eurobarometer 75.4 (ideal number of children, sociodemographic variables). Fertility is analyzed from 1960 until 2014. The main part of the thesis focuses on 2011, when census and opinion poll were conducted. Deeper analysis is performed by using cluster analysis and Poisson regression. The result of the thesis is the typology of fertility based on theories explaining fertility changes and empirical analysis. Keywords: fertility, typology, European Union, ideal number of children, cluster analysis, Poisson regression

[pt] A maioria das pesquisas sociais e de comportamento apresenta uma estrutura hierárquica, a qual pode ser caracterizada pela existência de agrupamento das unidades de análise. Nesta dissertação empregou-se modelos multiníveis aos dados de avaliação educacional do Sistema Nacional de Avaliação Básica (SAEB). O objetivo foi analisar a Repetência Escolar dos alunos de 4.a série do ensino fundamental na disciplina de matemática. Foram feitas regressões de Poisson com a variável Repetência como resposta e várias variáveis explicativas associadas ao aluno, professor e escola. Nos modelos foram considerados dois níveis de hierarquia (nível 1=aluno; nível 2=escola). Os trabalhos foram feitos no software Mlwin o qual possibilita o uso de dados multiníveis. / [en] The most of social and behaviour researches show hierarquical structure. In this dissertation, the evolution of education data s of Brazilian National System for the Evolution Education (SAEB) were used in the multilevel models. The aim was analysed repetence of students in the primary school in mathematics subject. Poisson Regressions were made with Repetence as response variable and a lot of explanatory variables were linked student, teacher and school. In this models were considered two hierarchy levels (1-student and 2-school). The procedures were made in the software Mlwin that allows using multileves data s. / [es] La mayoria de las investigaciones sociales y de comportamiento presentan una extructura jerárquica, que puede ser caracterizada por la existencia de agrupamientos de las unidades de análisis. En esta disertación se emplean modelos multiníveles en datos de evaluación educacional del Sistema Nacional de Evaluación Básica (SAEB). EL objetivo fue analizar la Repitencia Escolar de los alumnos de 4ª grado de la primaria (4ª série, ensino fundamental) en la disciplina de matemáticas. Se ajustaron regresiones de Poison utilizando con la variable Repitencia como respuesta y varias variables explicativas asociadas al alumno, profesor y escuela. En los modelos fueron considerados dos níveles de jerarquía (nivel 1=alumno; nivel 2=escola), utilizando el el software Mlwin, que es específico para el uso de datos multiníveles.

In this paper we study the occurrences of outdoor vehicle fires recorded by the Swedish Civil Contingencies Agency (MSB) for the period 1998-2019, and build static panel data models to predict future occurrences of fire in Stockholm County. Through comparing the performance of different models, we look at the effect of different distributional assumptions for the dependent variable on predictive performance. Our study concludes that treating the dependent variable as continuous does not hamper performance, with the exception of models meant to predict more uncommon occurrences of fire. Furthermore, we find that assuming that the dependent variable follows a Negative Binomial Distribution, rather than a Poisson Distribution, does not lead to substantial gains in performance, even in cases of overdispersion. Finally, we notice a slight increase in the number of vehicle fires shown in the data, and reflect on whether this could be related to the increased population size.

Factor score regression has recently received growing interest as an alternative for structural equation modelling. Two issues causing uncertainty for researchers are addressed in this thesis. Firstly, more knowledge is needed on how different approaches to calculating factor score estimates compare when estimating factor score regression models. Secondly, many applications are left without guidance because of the focus on normally distributed outcomes in the literature. This thesis examines how factor scoring methods compare when estimating regression coefficients in generalised linear factor score regression. An evaluation is made of the regression, correlation-preserving, total sum, and weighted sum method in ordinary, logistic, and Poisson factor score regression. In contrast to previous studies, both the mean and variance of loading coefficients and the degree of inter-factor correlation are varied in the simulations. A meta-analysis demonstrates that the choice of factor scoring method can substantially influence research conclusions. The regression and correlation-preserving method outperform the other two methods in terms of coefficient and standard error bias, accuracy, and empirical Type I error rates. Moreover, the regression method generally has the best performance. It is also noticed that performance can differ notably across the considered regression models.

Multiple regression models play an important role in analyzing and making predictions about data. Prediction accuracy becomes lower when two or more explanatory variables in the model are highly correlated. One solution is to use ridge regression. The purpose of this thesis is to study the performance of available ridge regression estimators for Poisson regression models in the presence of moderately to highly correlated variables. As performance criteria, we use mean square error (MSE), mean absolute percentage error (MAPE), and percentage of times the maximum likelihood (ML) estimator produces a higher MSE than the ridge regression estimator. A Monte Carlo simulation study was conducted to compare performance of the estimators under three experimental conditions: correlation, sample size, and intercept. It is evident from simulation results that all ridge estimators performed better than the ML estimator. We proposed new estimators based on the results, which performed very well compared to the original estimators. Finally, the estimators are illustrated using data on recreational habits.

Cultural competence is widely recognized as an essential strategy for reducing health disparities. As the United States' population becomes increasingly ethno-culturally diverse, these disparities are becoming even more pronounced. One particular challenge in this regard concerns overweight/obesity prevalence among American adults, as a disproportionately high number of racial and ethnic minority adults are classified as overweight or obese. Dietary behavior assessments are often utilized by health and human services professionals to obtain the data necessary to promote goals such as the reduction and elimination of overweight/obesity across all ethno-cultural groups. The primary objective of this research study was to develop, test, and evaluate a culturally-competent dietary behavior assessment instrument by effectively synthesizing qualitative methods from Cognitive Anthropology with appropriate survey research and quantitative statistical methods. Specifically, a quantitative methods triangle of hierarchical cluster analysis, binary logistic regression, and Poisson regression in conjunction with the free listing qualitative research technique from Cognitive Anthropology was explored as a possible combined methodological approach for researchers and public health professionals wishing to develop a comprehensive understanding of dietary behaviors at the local community level. Binary logistic regression and Poisson regression enabled the relationship between selected food categories and certain demographic/cultural indicators to be modeled, while hierarchical cluster analyses enabled modeling of the distinct patterns of food category groupings that comprise individuals' regular diet. Additionally, initial qualitative analyses of the raw data promoted an understanding of the influence that the local fast food and dine-in restaurant environment has on the dietary behaviors of the target population. The results of this study suggest that a quantitative methods triangle of hierarchical cluster analysis, binary logistic regression analysis, and Poisson regression analysis founded upon qualitative research principles has potential for use as a combined methodological approach for researchers and public health professionals wishing to develop a comprehensive understanding of dietary behaviors at the local community level. By employing these techniques, researchers can analyze individual dietary behaviors and eating patterns from a multifaceted perspective. In turn, public health professionals can develop community-based, cross-culturally relevant programs and interventions that are equally effective across all ethno-cultural groups in their target population.

Made available in DSpace on 2016-06-02T20:06:09Z (GMT). No. of bitstreams: 1 5822.pdf: 1106242 bytes, checksum: 613a82d7af4c6f40b60637e4c7122121 (MD5) Previous issue date: 2014-03-07 / Financiadora de Estudos e Projetos / In this dissertation, two models of probability distributions for the lifetimes until the occurrence of the event produced by a specific cause for elements in a population are reviewed. The first revised model is called the Weibull-Poisson (WP) which has been proposed by Louzada et al. (2011a). This model generalizes the exponential-Poisson distributions proposed by Kus (2007) and Weibull. The second, called long-term model, has been proposed by several authors and it considers that the population is not homogeneous in relation to the risk of event occurence by the cause studied. The population has a sub-population that consists of elements who are not liable do die by the specific cause in study. These elements are considered as immune or cured. In relation to the elements who are at risk the minimum value of time of the event accurance is observed. In the review of WP the expressions of the survival function, quantile function, probability density function, and of the hazard function, as well the expression of the non-central moments of order k and the distribution of order statistics are detailed. From this review we propose, in an original way, studies of the simulation to analyze the paramenters of frequentist properties of maximum likelihood estimators for this distribution. And also we also present results related to the inference about the parameters of this distribution, both in the case in which the data set consists of complete observations of lifetimes, and also in the case in which it may contain censored observations. Furthermore, we present in this paper, in an original way a regression model in a form of location and scale when T has WP distribution. Another original contribution of this dissertation is to propose the distribution of long-term Weibull-Poisson (LWP). Besides studying the LWP in the situation in which the covariates are included in the analysis. We also described the functions that characterize this distribution (distribution function, quantile function, probability density function and the hazard function). Moreover we describe the expression of the moment of order k, and the density function of a statistical order. A study by simulation viii of this distribution is made through maximum likelihood estimators. Applications to real data set illustrate the applicability of the two considered models. / Nesta dissertação são revistos dois modelos de distribuições de probabilidade para os tempos de vida até a ocorrência do evento provocado por uma causa específica para elementos em uma população. O primeiro modelo revisto é o denominado Weibull-Poisson (WP) que foi proposto por Louzada et al. (2011a), esse modelo generaliza as distribuições exponencial Poisson proposta por Kus (2007) e Weibull. O segundo, denominado modelo de longa duração, foi proposto por vários autores e considera que a população não é homogênea em relação ao risco de ocorrência do evento pela causa em estudo. A população possui uma sub-população constituída de elementos que não estão sujeitos ao evento pela causa especifica em estudo, sendo considerados como imunes ou curados. Em relação à parcela dos elementos que estão em risco observa-se o valor mínimo dos tempos da ocorrência do evento. Na revisão sobre a WP são detalhadas as expressões da função de sobrevivência, da função quantil, da função densidade de probabilidade e da função de risco, bem como a expressão dos momentos não centrais de ordem k e a distribuição de estatísticas de ordem. A partir desta revisão, é proposta de forma original, estudos de simulação com o objetivo de analisar as propriedades frequentistas dos estimadores de máxima verossimilhança dos parâmetros desta distribuição. E apresenta-se resultados relativos à inferência sobre os parâmetros desta distribuição, tanto no caso em que o conjunto de dados consta de observações completas de tempos de vida, como no caso em que ele possa conter observações censuradas. Alem disso, apresentamos de forma original neste trabalho um modelo de regressão na forma de locação e escala quando T tem distribuição WP. Outra contribuição original dessa dissertação é propor a distribuição de longa duração Weibull-Poisson (LWP), alem de estudar a LWP na situação em que as covariáveis são incluídas na análise. Realizou-se também a descrição das funções que caracterizam essa distribuição (função distribuição, função quantil, função densidade de probabilidade e função de risco). Assim como a descrição da expressão do momento de ordem k e da função densidade da estatística de ordem. É feito um estudo por simulação desta distribuição via máxima verossimilhança. Aplicações à conjuntos de dados reais ilustram a utilidade dos dois modelos considerados.

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本研究旨在探討國中教師的經師角色（投入教學）、人師角色（投入輔導）、導師角色（注重班級成績、注重班級整潔秩序）等變項對於國中生偏差行為的貫時性影響。研究資料取自中央研究院調查研究專題中心學術調查研究資料庫中的「台灣教育長期追蹤資料庫」第一波國中學生問卷【限制版原始數據】、第二波國中學生問卷【限制版原始數據】、第一波國中家長問卷【限制版原始數據】、第二波國中教師問卷【限制版原始數據】。 本研究又分為兩個子研究。研究一使用兩波問卷中的20,055筆國中生問卷及家長問卷，研究二使用兩波問卷中的8,794筆國中生問卷、家長問卷、導師問卷。本研究採用Rasch模式垂直等化、結構方程模式、階層卜瓦松模式分析資料，研究結果如下： 一、「人師角色」「經師角色」對國中生偏差行為影響的貫時性分析 （一）國一教師投入教學對於追蹤樣本國一學生偏差行為有顯著影響，教師越認真教學，學生偏差行為分數越低。 （二）國一教師投入教學對於追蹤樣本國三學生偏差行為有貫時性顯著影響，國一教師越認真教學，國三時追蹤樣本學生的偏差行為分數越低。 （三）國一二教師投入輔導對於追蹤樣本國三學生偏差行為有顯著影響，國一國二教師越投入輔導，追蹤樣本學生國三時的偏差行為分數越低。 二、「導師角色」對國中生偏差行為影響的貫時性分析 （一）追蹤樣本國三偏差行為顯著較該生國一時嚴重。 （二）偏差行為與性別有關，男生偏差行為分數顯著比女生高。 （三）追蹤樣本國一至國三偏差行為惡化程度與性別有關，男生偏差行為惡化情形顯著較女生嚴重。 （四）追蹤樣本國一至國三偏差行為惡化程度與該生國一時的學業成就有關。國一成績較差，國三偏差行為惡化程度顯著較嚴重。 （五）追蹤樣本國一至國三偏差行為惡化程度與該生國一時的讀書習慣有關。國一讀書習慣較差者，國三偏差行為惡化程度顯著較嚴重。 （六）導師要求班級學業成績，對於國中生偏差行為有顯著影響，導師越注重學業成績，該班學生偏差行為越低，且該影響具貫時性。 （七）導師要求班級整潔秩序等生活常規，對於國中生偏差行為有顯著影響，導師越要求班級整潔、秩序，該班學生偏差行為越低，且該影響具貫時性。 （八）國中生偏差行為與就讀學校公私立與否有關。私立學校學生偏差行為分數顯著較公立學校學生為低，且該影響具貫時性。 研究者並提出建議供教育實務工作者及教育主管單位參考。 / The purposes of the study were to explore teacher roles including instruction role, guidance role and headroom teacher’s role, and to find out the effects of teacher roles on junior high school students' deviant behavior. The data used in the analysis are from the nationally representative 2001–2003 Taiwan Education Panel Survey, including students’ questionnaire, students’ academic tests, parents’ questionnaire, and teachers’ questionnaire. In study 1, data from a 2-wave panel (N = 20,055), tested in the 7th and 9th grades, were used to estimate a structural equation model. The model was used to compose a previously observed teacher’s instruction role (teaching engagement) and guidance role (guidance engagement) in wave 1. In study 2, data also from a 2-wave panel (N=8,794), were to estimate a hierarchical Poisson regression model, in which independent variables were achievement-oriented headroom teacher role and discipline-oriented headroom teacher role, and dependent variable was students' deviant behavior. The results indicate that teachers who devoted themselves in teaching and guiding students could reduce junior high students’ deviant behavior, and the effects were longitudinal for at least 2 years. Also, both achievement-oriented and discipline-oriented headroom teachers could reduce junior high students’ deviant behavior, and the effects were longitudinal. Implications for current practice and future research are also discussed.

現今市場競爭愈來愈激烈，迫使廠商紛紛至海外尋求產品消費市場，在跨國銷售的背景之下，需要有更多可以確定國家選擇、預測銷售及估計需求的方法。而其中可以滿足這些需求的方法之中，就是研究產品跨國擴散型態，藉以瞭解後進國家與領先國家中新產品如何擴散且會如何互相影響 (Douglas and Craig, 1992)。 在眾多的跨國產品中，本研究選擇好萊塢電影做為實證分析的對象。 經由集群分析，本研究發現（一）台灣高首週票房且口碑佳的電影，會遇到假日人潮、有很高的美國總票房、以及很高的美國首週票房；（二）美國影片在美國及台灣映演的每週票房趨勢有差異存在；（三）片商沒有做好影片在台灣映演的檔期歸劃；（四）三群電影中，在影片類型沒有明顯地區別。 經由十二個新產品銷售預測模型的建立：對數線性迴歸模式（LN-Regression Model）（不考慮新產品領先國擴散經驗）（以OLS估計）、卜瓦松迴歸模式(Poisson Regression Model) （不考慮新產品領先國擴散經驗）（以MLE估計）、負二項分配迴歸模式(Negative Binomial Distribution Regression Model) （不考慮新產品領先國擴散經驗）（以MLE估計）、Exponential Decay模式（以OLS估計）＋迴歸方程式體系（不考慮新產品領先國擴散經驗）（以SUR估計）、Exponential Decay模式（以OLS估計）＋迴歸方程式體系（考慮新產品領先國擴散經驗）（以SUR估計）、Exponential Decay模式＋層級貝氏迴歸模式（考慮新產品領先國擴散經驗）、Bass連續型擴散模式（以NLS估計）＋迴歸方程式體系（不考慮新產品領先國擴散經驗（以SUR估計）、Bass連續型擴散模式（以NLS估計）＋迴歸方程式體系（考慮新產品領先國擴散經驗（以SUR估計）、Bass離散型擴散模式（以OLS估計）＋迴歸方程式體系（不考慮新產品領先國擴散經驗）（以SUR估計）、Bass離散型擴散模式（以OLS估計）＋迴歸方程式體系（考慮新產品領先國擴散經驗）（以SUR估計）、層級貝氏BASS離散型擴散模式＋迴歸方程式體系（不考慮新產品領先國擴散經驗）（以SUR估計）、層級貝氏BASS離散型擴散模式＋迴歸方程式體系（考慮新產品領先國擴散經驗）（以SUR估計）。本研究發現：（一）在考慮影響後進國的新產品擴散速度時，領先國的擴散經驗為絕對必要的考慮因子；（二）必須使用Bass連續型擴散模式做為建構新產品銷售預測模型的基礎；（三）必須使用Bass連續型擴散模式的NLS估計法估計Bass模型的創新係數p、模仿係數q及市場潛量m。