Um dos estudos observacionais mais difundidos e usados em epidemiologia veterinária é o estudo do tipo transversal. Sua popularidade ocorre por fatores como baixo custo e rapidez comparados com outros tipos de estudos, além de ajudar a estimar a prevalência de uma doença (desfecho) e postular fatores associados com o desfecho, que poderão ser confirmados como fatores causais em outros tipos de estudos epidemiológicos. Porém, este tipo de estudo apresenta dois importantes desafios: a dependência dos dados, muito frequente dada a típica estrutura populacional de animais dentro do mesmo rebanho ou fazenda e a escolha da medida de associação para desfechos binários, tão frequentes neste modelo de estudo. Com o objetivo de contribuir com a compreensão global da epidemiologia do aborto bovino associado à Neospora caninum tendo em conta a estrutura populacional, construiu-se um modelo misto com os dados de um estudo transversal realizado em duas regiões do Rio Grande do Sul. Usaram-se dados de 60 propriedades amostradas em duas regiões (noroeste e sudeste) e 1256 bovinos. A percentagem de aborto dentro de cada rebanho variou entre 1% e 30%. Vacas soropositivas tiveram 6,63 vezes mais chances de ter histórico de aborto (IC 95%: 4,41-13,20). As chances de uma vaca ter histórico de aborto foram 5,18 vezes maiores na região noroeste em relação à região sudeste (IC 95%: 1,83-20,80). Um coeficiente de correlação intraclasse de 16% foi estimado, indicando que 16% da variação da ocorrência de abortamentos não explicados pelos efeitos fixos foram devido as fazendas. Já na segunda parte deste trabalho, uma revisão sistemática foi realizada considerando um conjunto diverso de revistas e jornais com o objetivo de verificar os métodos estatísticos usados e a adequação das interpretações das medidas de associação estimadas em estudos transversais na área de medicina veterinária. Um total de 62 artigos foi avaliado. A revisão mostrou que, independentemente do nível de prevalência relatado no artigo, 96% deles empregou regressão logística e, portanto, estimaram razão de chances (RC). Nos artigos com prevalência superior a 10%, 23 deles fizeram uma interpretação adequada da RC como uma “razão de chances” ou simplesmente não fizeram uma interpretação direta da RC, enquanto 23 artigos interpretaram de forma inadequada a RC, considerando-a como risco ou probabilidade. Entre os artigos com prevalência inferior a 10%, apenas três interpretaram a RC como uma “razão de chances”, cinco interpretaram como risco ou probabilidade e em um, apesar de ter estimado a razão de prevalências (RP), foi interpretado de forma inadequada. Paralelamente, com o objetivo de exemplificar o uso de métodos estatísticos que estimam diretamente a razão de prevalências (RP), medida mais adequada para os estudos transversais, um conjunto de dados obtidos a partir de um estudo transversal sobre a ocorrência de anticorpos (AC) contra o vírus da diarreia viral bovina (BVDV) foi usado. Os AC foram medidos em amostras de tanque de leite de rebanhos leiteiros localizados no estado do Rio Grande do Sul, em que os possíveis fatores associados puderam ser avaliados. Entre os métodos utilizados, as maiores discrepâncias nas medidas de associação estimadas foram observadas com a regressão logística tomando-se como referência a regressão log-binomial. Finalmente, é importante que este tipo de desafio seja atendido pelos pesquisadores que realizam estudos transversais, ou seja, considerar a estrutura das populações nas análises, cuidado ao escolher o tipo de modelo estatístico empregado para desfecho binário e interpretação dos estimadores. / The commonest study design used in veterinary epidemiology is the cross-sectional study. Its popularity lies on the fact of the short time needed and low costs compared with other types of studies; moreover, this type of study estimates prevalence and associated factors, which may be elucidated as causal in another type of epidemiological studies. However, this type of study presents two major challenges: a very common dependence between data given the typical structure of the animal population, i.e., animals within herds or farms and the choice of measure of association for binary outcomes, frequently used in this type of study. In order to contribute to the understanding of the epidemiology of bovine abortion associated with Neospora caninum, a mixed model accounting for the hierarchical structure of cattle population using data from a cross-sectional study conducted in two regions (northwest and southeast) of Rio Grande do Sul was made. Data from 60 dairy herds and 1256 sampled cattle were used. The percentage of abortions in each herd ranged between 1% and 30%. Seropositive cows were 6.63 times more likely to have a history of abortion (95% CI: 4.41 to 13.20). The chances of a cow have a history of abortion were 5.18 times higher in the northwest comparing with the southeast region (95% CI: 1.83 to 20.80). An intraclass correlation coefficient (ICC) of 16% was estimated which means that 16% of the variation in abortion occurrence not explained by the fixed effects is due to farms. In the second part of this work, a systematic review was conducted considering a range of journals and newspapers in order to verify the statistical methods used and the adequacy of the interpretations of the measures of association estimated in cross-sectional studies from the veterinary medicine field. A total of 62 articles were revised. The review showed that, regardless of the reported prevalence, 96% of them employed logistic regression, therefore estimating odds ratio (OR). From the articles that reported prevalence rates above 10%, 23 of them did a proper interpretation of OR as an odds ratio, or simply did not make a direct interpretation of the OR, while 23 articles interpreted improperly the OR as a risk or probability. Among the articles that reported prevalence rates lower than 10%, only three interpreted the OR as an odds ratio, five interpreted as a risk or probability and only one, despite the estimated prevalence ratio (PR), it was improperly interpreted. Meanwhile, in order to exemplify the use of statistical methods to estimate directly the PR, the more appropriate measure of association in cross-sectional studies, a data set obtained from a cross-sectional study to estimate the occurrence of antibodies (AB) against bovine viral diarrhea virus (BVDV) in milk was used; AB were measured in bulk tank samples from dairy herds located in the state of Rio Grande do Sul, Brazil, and also possible associated factors were estimated. Among the methods used, major discrepancies in the measures of association estimated were observed with the logistic regression, comparing with the log-binomial regression. Finally, it is important that such challenges are met by the researchers that undertake cross-sectional studies.

L’objectif des essais de phase I en oncologie est d’identifier la dose maximale tolérée (DMT). Le schéma « 3+3 » nécessite d’interrompre les inclusions en attendant l’évaluation d’une cohorte de trois patients pour définir la dose à attribuer aux patients suivants. Les investigateurs d’oncologie pédiatrique ont proposé l’adaptation Rolling 6 pour éviter cette suspension temporaire des inclusions. Dans une étude de simulation, nous avons montré qu’un schéma adaptatif avec attribution des doses basées sur un modèle statistique permettait de pallier ce problème, et identifiait plus fréquemment la DMT. Néanmoins ces trois schémas restent limités pour identifier la DMT, notamment du fait que le critère de jugement est un critère binaire, la survenue de toxicité dose-limitante sur un cycle de traitement. Nous avons proposé un nouveau schéma adaptatif utilisant les données ordinales répétées de toxicité sur l’ensemble des cycles de traitement. La dose à identifier est celle associée au taux de toxicité grave maximal par cycle que l’on juge tolérable. Le grade maximal de toxicité par cycle de traitement, en 3 catégories (grave / modéré / nul), a été modélisé par le modèle mixte à cotes proportionnelles. Le modèle est performant à la fois pour détecter un effet cumulé dans le temps et améliore l’identification de la dose cible, sans risque majoré de toxicité, et sans rallonger la durée des essais. Nous avons aussi étudié l’intérêt de ce modèle ordinal par rapport à un modèle logistique mixte plus parcimonieux. Ces modèles pour données longitudinales devraient être plus souvent utilisés pour l’analyse des essais de phase I étant donné leur pertinence et la faisabilité de leur implémentation. / Phase I dose-finding trials aim at identifying the maximum tolerated dose (MTD). The “3+3” design requires an interruption of enrolment while the evaluation of the previous three patients is pending. In pediatric oncology, investigators proposed the Rolling 6 design to allow for a more continuous enrollment. In a simulation study, we showed that an adaptive dose-finding design, with dose allocation guided by a statistical model not only minimizes accrual suspension as with the rolling 6, and but also led to identify more frequently the MTD. However, the performance of these designs in terms of correct identification of the MTD is limited by the binomial variability of the main outcome: the occurrence of dose-limiting toxicity over the first cycle of treatment. We have then proposed a new adaptive design using repeated ordinal data of toxicities experienced during all the cycles of treatment. We aim at identifying the dose associated with a specified tolerable probability of severe toxicity per cycle. The outcome was expressed as the worst toxicity experienced, in three categories (severe / moderate / no toxicity), repeated at each treatment cycle. It was modeled through a proportional odds mixed model. This model enables to seek for cumulated toxicity with time, and to increase the ability to identify the targeted dose, with no increased risk of toxicity, and without delaying study completion. We also compared this ordinal model to a more parsimonious logistic mixed model.Because of their applicability and efficiency, those models for longitudinal data should be more often used in phase I dose-finding trials.

iv Abstract This thesis uncovers the long-term development of overweight and obesity prevalence in the Czech Republic and finds the associations with relevant lifestyle risk factors and determinants of health. Periodically collected interview and examination survey data from 1993 to 2019 are standardised and used to perform a pooled analysis to inspect trends within the cross-sectional units. The binomial logistic regression is used to estimate changes in the odds of being overweight given a set of socio-economic and lifestyle-related predictors, and to inspect time trends in their magnitude and significance. Adjustment to historical data is calculated to account for methodological changes in BMI classification scheme to ensure comparability of survey outcomes. In addition, the response bias in self-reported anthropometric measurements is confirmed and quantified. Finally, the most recent data (2019) for obesity rates are updated accordingly to reflect this finding. The true prevalence of overweight in the Czech adult population is calculated to 75.8% for men and 58.8% for women, which is higher than interview survey results by 7.7 and 9.6 percentage points respectively. These adjusted results may be utilised by users of survey outcomes to build their analyses on validated data, together with other...

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Studien syftar till att undersöka vilken förvaltningsstrategi som är bäst, fonders prestation genom olika ekonomiska förhållanden samt persistens på den svenska fondmarknaden. Huvudsyftet är att undersöka om fonders föregående prestation kan användas för att förutsäga framtida avkastning. Genom att använda etablerade mått på förvaltningsprestation som Jensens Alfa, Sharpekvoten och Modiglianis riskjusterad prestation (𝑀2) jämförs fonders prestation. För att identifiera persistens jämförs fondernas avkastning med medianavkastning under en specifik period. Genom statistiska tester i form av Oddskvot, Chi-två-test och regressionsanalys fördjupas studien ytterligare. Resultaten från studien visar enskilda fall av persistens, men inga konsekventa mönster kan utläsas för alla fonder. Slutsatsen från studien är att det inte går att slå fast en överlägsen förvaltningsstrategi. Slutsatsen indikerar även att det inte finns några signifikanta indikationer på att det går att förutspå framtida avkastning utifrån föregående tidsperiods avkastning. / The study investigates which management strategy is superior, funds’ performance across different economic conditions and persistence in the Swedish fund market. The main objective is to examine whether past fund performance can be utilized to predict future returns. Through using established performance measures such as Jensen’s Alpha, The Sharpe Ratio and Modigliani’s risk- adjusted performance (𝑀2), we compare fund performance. To identify persistence, funds’ returns are compared with median returns over a specific period. Through statistical tests such as Odds Ratio, Chi-square test and regression analysis, the study is further elaborated. The results of the study reveal isolated instances of persistence, but no consistent patterns can be discerned across all funds. The conclusion drawn from the study is that no superior management strategy can be definitively established. Additionally, the findings suggest no significant indications that past period returns can predict future returns.

This thesis presents work around 3 themes: dark energy, gravitational waves and Bayesian inference. Both dark energy and gravitational wave physics are not yet well constrained. They present interesting challenges for Bayesian inference, which attempts to quantify our knowledge of the universe given our astrophysical data. A dark energy equation of state reconstruction analysis finds that the data favours the vacuum dark energy equation of state $w {=} -1$ model. Deviations from vacuum dark energy are shown to favour the super-negative ‘phantom’ dark energy regime of $w {< } -1$, but at low statistical significance. The constraining power of various datasets is quantified, finding that data constraints peak around redshift $z = 0.2$ due to baryonic acoustic oscillation and supernovae data constraints, whilst cosmic microwave background radiation and Lyman-$\alpha$ forest constraints are less significant. Specific models with a conformal time symmetry in the Friedmann equation and with an additional dark energy component are tested and shown to be competitive to the vacuum dark energy model by Bayesian model selection analysis: that they are not ruled out is believed to be largely due to poor data quality for deciding between existing models. Recent detections of gravitational waves by the LIGO collaboration enable the first gravitational wave tests of general relativity. An existing test in the literature is used and sped up significantly by a novel method developed in this thesis. The test computes posterior odds ratios, and the new method is shown to compute these accurately and efficiently. Compared to computing evidences, the method presented provides an approximate 100 times reduction in the number of likelihood calculations required to compute evidences at a given accuracy. Further testing may identify a significant advance in Bayesian model selection using nested sampling, as the method is completely general and straightforward to implement. We note that efficiency gains are not guaranteed and may be problem specific: further research is needed.

Therapeutic horseback riding (THR) uses the horse as a therapeutic apparatus in physical and psychological therapy. This dissertation suggests a more appropriate technique for measuring the effect of THR. A research survey of the statistical methods used to determine the effect of THR was undertaken. Although researchers observed clinically meaningful change in several of the studies, this was not supported by statistical tests. A logistic regression approach is proposed as a solution to many of the problems experienced by researchers on THR. Since large THR related data sets are not available, data were simulated. Logistic regression and t-tests were used to analyse the same simulated data sets, and the results were compared. The advantages of the logistic regression approach are discussed. This statistical technique can be applied in any field where the therapeutic value of an intervention has to be proven scientifically. / Mathematical Sciences / M. Sc. (Statistics)

Michel Maffesoli and Zygmunt Bauman add the traits of Benjamin's flâneur to the (neo-)nomad, namely his "flâneur" gaze and his relation to commodities. But in the concept of nomad these traits gain specific nature - on the field of fashion they transform nomad into migrant, who is capable of creative work with vanitas. Nomad as a travelling flâneur is a stranger-guest and becomes a tourist, willingly getting lost in the city and voluntarily being surprised by unexpected encounters. Tourists relation to his memories could be described with Benjamin's description of mémoire involontaire as a revived punctum. A tourist prepares his memories like a nicely descending ruins. Souvenir is his materialised memory. It's not only a duplicated plastic Eiffel tower, but a magic artifact. It's a collective aura, what's on Benjamin's mind when he writes about aura regression. The private aura comes instead, turning things to talismans, reenchanting the world. The era of postmechanical reproduction reminds one, that there is a way to reproduce not just mechanically but biologically: a bricolage remix is made. Souvenirs descend and take shape of hommogenic rummage which reveals the fundamental form of postmodern metamorphosis: recyclation. This metamorphosis can finally be used when analyzing the settler turn into nomad...

Thesis "Data Mining in the Field of English Football League Third Division's Betting Odds" deals with data mining referring to acquiring knowledge from data. The main objective of this work is to develop data models for prediction of match results and to compare these predictions with a chosen strategy of betting. The selected betting strategy is based on betting single bets with odds belonging to chosen intervals, which generate a profit. These odds intervals were discovered by analyzing 2006-2009 football matches in a created simulator. On the basis of these odds ranges data models were constructed. Each data model contains a hypothesis which is generated by SD4ft procedure of LispMiner based on all football matches played in seasons 2001-2008. Developed data models are tested afterwards using 2006-2009 football matches data. Results show that all derived data models are profitable in all four seasons under consideration. More than half of them successfully predicted 2009 matches as well. The analysis showed that betting agencies offer mostly odds which make it almost impossible to be profitable while betting on matches according to their odds. In spite of this fact I identified some odds intervals with which you can success while betting single bets on home-team, draw or visitor-team with odds falling within these intervals. Association rules with reasonable confidence and support can generate high profitability. It is important to realize that there are no data models which guarantee a certain profit. Most of developed data models are not applicable in the real world, some of them can actually generate a loss. Nevertheless there are data models to be found that could generate a profit in the real world.