Das conceções às práticas de avaliação formativa no 1.º ciclo do ensino básico

Relatório de estágio apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ensino do 1.º e 2.º Ciclo do Ensino Básico

On sampling collection procedure effectiveness for forest soil characterization

One of the most important measures to prevent wild forest fires is the use of prescribed and controlled burning actions as it reduce the fuel mass availability. The impact of these management activities on soil physical and chemical properties varies according to the type of both soil and vegetation. Decisions in forest management plans are often based on the results obtained from soil-monitoring campaigns. Those campaigns are often man-labor intensive and expensive. In this paper we have successfully used the multivariate statistical technique Robust Principal Analysis Compounds (ROBPCA) to investigate on the sampling procedure effectiveness for two different methodologies, in order to reflect on the possibility of simplifying and reduce the sampling collection process and its auxiliary laboratory analysis work towards a cost-effective and competent forest soil characterization.

Genetics of berry colour and anthocyanin content variation in grapevine (Vitis vinifera L.subsp. vinifera)

Dissertation presented in fulfillment of the requirements for the Degree of Doctor of Philosophy in Biology (Molecular Genetics) at the Instituto de Tecnologia Química e Biológica da Universidade Nova de Lisboa

Exploraty Multivariate Statistical Methods Applied to Pharmaceutical Industry CRM Data

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Métodos estatísticos aplicados à modelação de dados oncológicos

RESUMO: A estrutura demográfica portuguesa é marcada por baixas taxas de natalidade e mortalidade, onde a população idosa representa uma fatia cada vez mais representativa, fruto de uma maior longevidade. A incidência do cancro, na sua generalidade, é maior precisamente nessa classe etária. A par de outras doenças igualmente lesivas (e.g. cardiovasculares, degenerativas) cuja incidência aumenta com a idade, o cancro merece relevo. Estudos epidemiológicos apresentam o cancro como líder mundial na mortalidade. Em países desenvolvidos, o seu peso representa 25% do número total de óbitos, percentagem essa que mais que duplica noutros países. A obesidade, a baixa ingestão de frutas e vegetais, o sedentarismo, o consumo de tabaco e a ingestão de álcool, configuram-se como cinco dos fatores de risco presentes em 30% das mortes diagnosticadas por cancro. A nível mundial e, em particular no Sul de Portugal, os cancros do estômago, recto e cólon apresentam elevadas taxas de incidência e de mortalidade. Do ponto de vista estritamente económico, o cancro é a doença que mais recursos consome enquanto que do ponto de vista físico e psicológico é uma doença que não limita o seu raio de ação ao doente. O cancro é, portanto, uma doença sempre atual e cada vez mais presente, pois reflete os hábitos e o ambiente de uma sociedade, não obstante as características intrínsecas a cada indivíduo. A adoção de metodologia estatística aplicada à modelação de dados oncológicos é, sobretudo, valiosa e pertinente quando a informação é oriunda de Registos de Cancro de Base Populacional (RCBP). A pertinência é justificada pelo fato destes registos permitirem aferir numa população específica, o risco desta sofrer e/ou vir a sofrer de uma dada neoplasia. O peso que as neoplasias do estômago, cólon e recto assumem foi um dos elementos que motivou o presente estudo que tem por objetivo analisar tendências, projeções, sobrevivências relativas e a distribuição espacial destas neoplasias. Foram considerados neste estudo todos os casos diagnosticados no período 1998-2006, pelo RCBP da região sul de Portugal (ROR-Sul). O estudo descritivo inicial das taxas de incidência e da tendência em cada uma das referidas neoplasias teve como base uma única variável temporal - o ano de diagnóstico - também designada por período. Todavia, uma metodologia que contemple apenas uma única variável temporal é limitativa. No cancro, para além do período, a idade à data do diagnóstico e a coorte de nascimento, são variáveis temporais que poderão prestar um contributo adicional na caracterização das taxas de incidência. A relevância assumida por estas variáveis temporais justificou a sua inclusão numaclasse de modelos designada por modelos Idade-Período-Coorte (Age-Period-Cohort models - APC), utilizada na modelação das taxas de incidência para as neoplasias em estudo. Os referidos modelos permitem ultrapassar o problema de relações não lineares e/ou de mudanças súbitas na tendência linear das taxas. Nos modelos APC foram consideradas a abordagem clássica e a abordagem com recurso a funções suavizadoras. A modelação das taxas foi estratificada por sexo. Foram ainda estudados os respectivos submodelos (apenas com uma ou duas variáveis temporais). Conhecido o comportamento das taxas de incidência, uma questão subsequente prende-se com a sua projeção em períodos futuros. Porém, o efeito de mudanças estruturais na população, ao qual Portugal não é alheio, altera substancialmente o número esperado de casos futuros com cancro. Estimativas da incidência de cancro a nível mundial obtidas a partir de projeções demográficas apontam para um aumento de 25% dos casos de cancro nas próximas duas décadas. Embora a projeção da incidência esteja associada a alguma incerteza, as projeções auxiliam no planeamento de políticas de saúde para a afetação de recursos e permitem a avaliação de cenários e de intervenções que tenham como objetivo a redução do impacto do cancro. O desconhecimento de projeções da taxa de incidência destas neoplasias na área abrangida pelo ROR-Sul, levou à utilização de modelos de projeção que diferem entre si quanto à sua estrutura, linearidade (ou não) dos seus coeficientes e comportamento das taxas na série histórica de dados (e.g. crescente, decrescente ou estável). Os referidos modelos pautaram-se por duas abordagens: (i)modelos lineares no que concerne ao tempo e (ii) extrapolação de efeitos temporais identificados pelos modelos APC para períodos futuros. Foi feita a projeção das taxas de incidência para os anos de 2007 a 2010 tendo em conta o género, idade e neoplasia. É ainda apresentada uma estimativa do impacto económico destas neoplasias no período de projeção. Uma questão pertinente e habitual no contexto clínico e a que o presente estudo pretende dar resposta, reside em saber qual a contribuição da neoplasia em si para a sobrevivência do doente. Nesse sentido, a mortalidade por causa específica é habitualmente utilizada para estimar a mortalidade atribuível apenas ao cancro em estudo. Porém, existem muitas situações em que a causa de morte é desconhecida e, mesmo que esta informação esteja disponível através dos certificados de óbito, não é fácil distinguir os casos em que a principal causa de morte é devida ao cancro. A sobrevivência relativa surge como uma medida objetiva que não necessita do conhecimento da causa específica da morte para o seu cálculo e dar-nos-á uma estimativa da probabilidade de sobrevivência caso o cancro em análise, num cenário hipotético, seja a única causa de morte. Desconhecida a principal causa de morte nos casos diagnosticados com cancro no registo ROR-Sul, foi determinada a sobrevivência relativa para cada uma das neoplasias em estudo, para um período de follow-up de 5 anos, tendo em conta o sexo, a idade e cada uma das regiões que constituem o registo. Foi adotada uma análise por período e as abordagens convencional e por modelos. No epílogo deste estudo, é analisada a influência da variabilidade espaço-temporal nas taxas de incidência. O longo período de latência das doenças oncológicas, a dificuldade em identificar mudanças súbitas no comportamento das taxas, populações com dimensão e riscos reduzidos, são alguns dos elementos que dificultam a análise da variação temporal das taxas. Nalguns casos, estas variações podem ser reflexo de flutuações aleatórias. O efeito da componente temporal aferida pelos modelos APC dá-nos um retrato incompleto da incidência do cancro. A etiologia desta doença, quando conhecida, está associada com alguma frequência a fatores de risco tais como condições socioeconómicas, hábitos alimentares e estilo de vida, atividade profissional, localização geográfica e componente genética. O “contributo”, dos fatores de risco é, por vezes, determinante e não deve ser ignorado. Surge, assim, a necessidade em complementar o estudo temporal das taxas com uma abordagem de cariz espacial. Assim, procurar-se-á aferir se as variações nas taxas de incidência observadas entre os concelhos inseridos na área do registo ROR-Sul poderiam ser explicadas quer pela variabilidade temporal e geográfica quer por fatores socioeconómicos ou, ainda, pelos desiguais estilos de vida. Foram utilizados os Modelos Bayesianos Hierárquicos Espaço-Temporais com o objetivo de identificar tendências espaço-temporais nas taxas de incidência bem como quantificar alguns fatores de risco ajustados à influência simultânea da região e do tempo. Os resultados obtidos pela implementação de todas estas metodologias considera-se ser uma mais valia para o conhecimento destas neoplasias em Portugal.------------ABSTRACT: mortality rates, with the elderly being an increasingly representative sector of the population, mainly due to greater longevity. The incidence of cancer, in general, is greater precisely in that age group. Alongside with other equally damaging diseases (e.g. cardiovascular,degenerative), whose incidence rates increases with age, cancer is of special note. In epidemiological studies, cancer is the global leader in mortality. In developed countries its weight represents 25% of the total number of deaths, with this percentage being doubled in other countries. Obesity, a reduce consumption of fruit and vegetables, physical inactivity, smoking and alcohol consumption, are the five risk factors present in 30% of deaths due to cancer. Globally, and in particular in the South of Portugal, the stomach, rectum and colon cancer have high incidence and mortality rates. From a strictly economic perspective, cancer is the disease that consumes more resources, while from a physical and psychological point of view, it is a disease that is not limited to the patient. Cancer is therefore na up to date disease and one of increased importance, since it reflects the habits and the environment of a society, regardless the intrinsic characteristics of each individual. The adoption of statistical methodology applied to cancer data modelling is especially valuable and relevant when the information comes from population-based cancer registries (PBCR). In such cases, these registries allow for the assessment of the risk and the suffering associated to a given neoplasm in a specific population. The weight that stomach, colon and rectum cancers assume in Portugal was one of the motivations of the present study, that focus on analyzing trends, projections, relative survival and spatial distribution of these neoplasms. The data considered in this study, are all cases diagnosed between 1998 and 2006, by the PBCR of Portugal, ROR-Sul.Only year of diagnosis, also called period, was the only time variable considered in the initial descriptive analysis of the incidence rates and trends for each of the three neoplasms considered. However, a methodology that only considers one single time variable will probably fall short on the conclusions that could be drawn from the data under study. In cancer, apart from the variable period, the age at diagnosis and the birth cohort are also temporal variables and may provide an additional contribution to the characterization of the incidence. The relevance assumed by these temporal variables justified its inclusion in a class of models called Age-Period-Cohort models (APC). This class of models was used for the analysis of the incidence rates of the three cancers under study. APC models allow to model nonlinearity and/or sudden changes in linear relationships of rate trends. Two approaches of APC models were considered: the classical and the one using smoothing functions. The models were stratified by gender and, when justified, further studies explored other sub-models where only one or two temporal variables were considered. After the analysis of the incidence rates, a subsequent goal is related to their projections in future periods. Although the effect of structural changes in the population, of which Portugal is not oblivious, may substantially change the expected number of future cancer cases, the results of these projections could help planning health policies with the proper allocation of resources, allowing for the evaluation of scenarios and interventions that aim to reduce the impact of cancer in a population. Worth noting that cancer incidence worldwide obtained from demographic projections point out to an increase of 25% of cancer cases in the next two decades. The lack of projections of incidence rates of the three cancers under study in the area covered by ROR-Sul, led us to use a variety of forecasting models that differ in the nature and structure. For example, linearity or nonlinearity in their coefficients and the trend of the incidence rates in historical data series (e.g. increasing, decreasing or stable).The models followed two approaches: (i) linear models regarding time and (ii) extrapolation of temporal effects identified by the APC models for future periods. The study provide incidence rates projections and the numbers of newly diagnosed cases for the year, 2007 to 2010, taking into account gender, age and the type of cancer. In addition, an estimate of the economic impact of these neoplasms is presented for the projection period considered. This research also try to address a relevant and common clinical question in these type of studies, regarding the contribution of the type of cancer to the patient survival. In such studies, the primary cause of death is commonly used to estimate the mortality specifically due to the cancer. However, there are many situations in which the cause of death is unknown, or, even if this information is available through the death certificates, it is not easy to distinguish the cases where the primary cause of death is the cancer. With this in mind, the relative survival is an alternative measure that does not need the knowledge of the specific cause of death to be calculated. This estimate will represent the survival probability in the hypothetical scenario of a certain cancer be the only cause of death. For the patients with unknown cause of death that were diagnosed with cancer in the ROR-Sul, the relative survival was calculated for each of the cancers under study, for a follow-up period of 5 years, considering gender, age and each one of the regions that are part the registry. A period analysis was undertaken, considering both the conventional and the model approaches. In final part of this study, we analyzed the influence of space-time variability in the incidence rates. The long latency period of oncologic diseases, the difficulty in identifying subtle changes in the rates behavior, populations of reduced size and low risk are some of the elements that can be a challenge in the analysis of temporal variations in rates, that, in some cases, can reflect simple random fluctuations. The effect of the temporal component measured by the APC models gives an incomplete picture of the cancer incidence. The etiology of this disease, when known, is frequently associated to risk factors such as socioeconomic conditions, eating habits and lifestyle, occupation, geographic location and genetic component. The "contribution"of such risk factors is sometimes decisive in the evolution of the disease and should not be ignored. Therefore, there was the need to consider an additional approach in this study, one of spatial nature, addressing the fact that changes in incidence rates observed in the ROR-Sul area, could be explained either by temporal and geographical variability or by unequal socio-economic or lifestyle factors. Thus, Bayesian hierarchical space-time models were used with the purpose of identifying space-time trends in incidence rates together with the the analysis of the effect of the risk factors considered in the study. The results obtained and the implementation of all these methodologies are considered to be an added value to the knowledge of these neoplasms in Portugal.

Statistical hypothesis testing and common misinterpretations: should we abandon p-value in forensic science applications?

Many people regard the concept of hypothesis testing as fundamental to inferential statistics. Various schools of thought, in particular frequentist and Bayesian, have promoted radically different solutions for taking a decision about the plausibility of competing hypotheses. Comprehensive philosophical comparisons about their advantages and drawbacks are widely available and continue to span over large debates in the literature. More recently, controversial discussion was initiated by an editorial decision of a scientific journal [1] to refuse any paper submitted for publication containing null hypothesis testing procedures. Since the large majority of papers published in forensic journals propose the evaluation of statistical evidence based on the so called p-values, it is of interest to expose the discussion of this journal's decision within the forensic science community. This paper aims to provide forensic science researchers with a primer on the main concepts and their implications for making informed methodological choices.

An exploration of the experience of implementing the second step violence prevention curriculum in one primary general learning disabilities class /

Violence has always been a part of the human experience, and therefore, a popular topic for research. It is a controversial issue, mostly because the possible sources of violent behaviour are so varied, encompassing both biological and environmental factors. However, very little disagreement is found regarding the severity of this societal problem. Most researchers agree that the number and intensity of aggressive acts among adults and children is growing. Not surprisingly, many educational policies, programs, and curricula have been developed to address this concern. The research favours programs which address the root causes of violence and seek to prevent rather than provide consequences for the undesirable behaviour. But what makes a violence prevention program effective? How should educators choose among the many curricula on the market? After reviewing the literature surrounding violence prevention programs and their effectiveness, The Second Step Violence Prevention Curriculum surfaced as unique in many ways. It was designed to address the root causes of violence in an active, student-centred way. Empathy training, anger management, interpersonal cognitive problem solving, and behavioural social skills form the basis of this program. Published in 1992, the program has been the topic of limited research, almost entirely carried out using quantitative methodologies.The purpose of this study was to understand what happens when the Second Step Violence Prevention Curriculum is implemented with a group of students and teachers. I was not seeking a statistical correlation between the frequency of violence and program delivery, as in most prior research. Rather, I wished to gain a deeper understanding of the impact ofthe program through the eyes of the participants. The Second Step Program was taught to a small, primary level, general learning disabilities class by a teacher and student teacher. Data were gathered using interviews with the teachers, personal observations, staff reports, and my own journal. Common themes across the four types of data collection emerged during the study, and these themes were isolated and explored for meaning. Findings indicate that the program does not offer a "quick fix" to this serious problem. However, several important discoveries were made. The teachers feU that the program was effective despite a lack of concrete evidence to support this claim. They used the Second Step strategies outside their actual instructional time and felt it made them better educators and disciplinarians. The students did not display a marked change in their behaviour during or after the program implementation, but they were better able to speak about their actions, the source of their aggression, and the alternatives which were available. Although they were not yet transferring their knowledge into positive action,a heightened awareness was evident. Finally, staff reports and my own journal led me to a deeper understanding ofhow perception frames reality. The perception that the program was working led everyone to feel more empowered when a violent incident occurred, and efforts were made to address the cause rather than merely to offer consequences. A general feeling that we were addressing the problem in a productive way was prevalent among the staff and students involved. The findings from this investigation have many implications for research and practice. Further study into the realm of violence prevention is greatly needed, using a balance of quantitative and qualitative methodologies. Such a serious problem can only be effectively addressed with a greater understanding of its complexities. This study also demonstrates the overall positive impact of the Second Step Violence Prevention Curriculum and, therefore, supports its continued use in our schools.

Modified statistical methods to calculate rare gas interaction potentials

New density functionals representing the exchange and correlation energies (per electron) are employed, based on the electron gas model, to calculate interaction potentials of noble gas systems X2 and XY, where X (and Y) are He,Ne,Ar and Kr, and of hydrogen atomrare gas systems H-X. The exchange energy density functional is that recommended by Handler and the correlation energy density functional is a rational function involving two parameters which were optimized to reproduce the correlation energy of He atom. Application of the two parameter function to other rare gas atoms shows that it is "universal"; i. e. ,accurate for the systems considered. The potentials obtained in this work compare well with recent experimental results and are a significant improvement over those from competing statistical modelS.

On the path integral formulation and the evaluation of quantum statistical averages

Four problems of physical interest have been solved in this thesis using the path integral formalism. Using the trigonometric expansion method of Burton and de Borde (1955), we found the kernel for two interacting one dimensional oscillators• The result is the same as one would obtain using a normal coordinate transformation, We next introduced the method of Papadopolous (1969), which is a systematic perturbation type method specifically geared to finding the partition function Z, or equivalently, the Helmholtz free energy F, of a system of interacting oscillators. We applied this method to the next three problems considered• First, by summing the perturbation expansion, we found F for a system of N interacting Einstein oscillators^ The result obtained is the same as the usual result obtained by Shukla and Muller (1972) • Next, we found F to 0(Xi)f where A is the usual Tan Hove ordering parameter* The results obtained are the same as those of Shukla and Oowley (1971), who have used a diagrammatic procedure, and did the necessary sums in Fourier space* We performed the work in temperature space• Finally, slightly modifying the method of Papadopolous, we found the finite temperature expressions for the Debyecaller factor in Bravais lattices, to 0(AZ) and u(/K/ j,where K is the scattering vector* The high temperature limit of the expressions obtained here, are in complete agreement with the classical results of Maradudin and Flinn (1963) .

Statistical Inference for Computable General Equilibrium Models with Application to a Model of the Moroccan Economy

We study the problem of measuring the uncertainty of CGE (or RBC)-type model simulations associated with parameter uncertainty. We describe two approaches for building confidence sets on model endogenous variables. The first one uses a standard Wald-type statistic. The second approach assumes that a confidence set (sampling or Bayesian) is available for the free parameters, from which confidence sets are derived by a projection technique. The latter has two advantages: first, confidence set validity is not affected by model nonlinearities; second, we can easily build simultaneous confidence intervals for an unlimited number of variables. We study conditions under which these confidence sets take the form of intervals and show they can be implemented using standard methods for solving CGE models. We present an application to a CGE model of the Moroccan economy to study the effects of policy-induced increases of transfers from Moroccan expatriates.

Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments

It is well known that standard asymptotic theory is not valid or is extremely unreliable in models with identification problems or weak instruments [Dufour (1997, Econometrica), Staiger and Stock (1997, Econometrica), Wang and Zivot (1998, Econometrica), Stock and Wright (2000, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. One possible way out consists here in using a variant of the Anderson-Rubin (1949, Ann. Math. Stat.) procedure. The latter, however, allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, which in general does not allow for individual coefficients. This problem may in principle be overcome by using projection techniques [Dufour (1997, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. AR-types are emphasized because they are robust to both weak instruments and instrument exclusion. However, these techniques can be implemented only by using costly numerical techniques. In this paper, we provide a complete analytic solution to the problem of building projection-based confidence sets from Anderson-Rubin-type confidence sets. The latter involves the geometric properties of “quadrics” and can be viewed as an extension of usual confidence intervals and ellipsoids. Only least squares techniques are required for building the confidence intervals. We also study by simulation how “conservative” projection-based confidence sets are. Finally, we illustrate the methods proposed by applying them to three different examples: the relationship between trade and growth in a cross-section of countries, returns to education, and a study of production functions in the U.S. economy.

Identification, Weak Instruments and Statistical Inference in Econometrics

We discuss statistical inference problems associated with identification and testability in econometrics, and we emphasize the common nature of the two issues. After reviewing the relevant statistical notions, we consider in turn inference in nonparametric models and recent developments on weakly identified models (or weak instruments). We point out that many hypotheses, for which test procedures are commonly proposed, are not testable at all, while some frequently used econometric methods are fundamentally inappropriate for the models considered. Such situations lead to ill-defined statistical problems and are often associated with a misguided use of asymptotic distributional results. Concerning nonparametric hypotheses, we discuss three basic problems for which such difficulties occur: (1) testing a mean (or a moment) under (too) weak distributional assumptions; (2) inference under heteroskedasticity of unknown form; (3) inference in dynamic models with an unlimited number of parameters. Concerning weakly identified models, we stress that valid inference should be based on proper pivotal functions —a condition not satisfied by standard Wald-type methods based on standard errors — and we discuss recent developments in this field, mainly from the viewpoint of building valid tests and confidence sets. The techniques discussed include alternative proposed statistics, bounds, projection, split-sampling, conditioning, Monte Carlo tests. The possibility of deriving a finite-sample distributional theory, robustness to the presence of weak instruments, and robustness to the specification of a model for endogenous explanatory variables are stressed as important criteria assessing alternative procedures.