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This thesis provides insights into the creation of a model for predicting odds in the Premier League. It illustrates how the ELO system and historical odds, in combination with Monte Carlo simulations, can be implemented through logistic regression to predict odds in an unbiased way. The findings are that the model performs generally well, but significantly worse at the beginning and end of the Premier League seasons. For further improvements, it is most likely necessary to factor in variables not available in the current model. Such factors could for example be incentives, injuries, or changes in the squad, all not being accounted for by the model in this case. / Detta examensarbete ger insikter om skapandet av en modell för att förutsäga oddsen i Premier League. Den visar hur ELO-systemet och historiska odds, i kombination med Monte Carlo-simuleringar, kan implementeras genom logistisk regression för att förutsäga oddsen på ett opartiskt sätt. Resultaten visar att modellen generellt sett fungerar bra, men betydligt sämre i början och slutet av Premier League-säsongerna. För ytterligare förbättringar är det troligtvis nödvändigt att ta hänsyn till variabler som inte är tillgängliga i den nuvarande modellen. Sådana faktorer kan till exempel vara incitament, skador eller förändringar i truppen, som alla inte tas hänsyn till i modellen i detta fall.

Cancer is a highly prevalent disease worldwide, claiming hundreds of lives each year. In the field of cancer research, it is customary to conduct surveys in which patients are asked to self-report and assess their symptoms and overall health. In such research, it is essential for patients to respond promptly to questionnaires to avoid recall bias and for a representative patient sample to respond to avoid biased sampling. This report aims to investigate the factors that impact response rate and response time using logistic regression and Poisson regression. The study focuses on a dataset of patients with colorectal cancer, with the response rate of patients with pancreatic cancer serving as a reference. By analyzing variables such as gender, age, place of residence, and the method of survey notification, the conclusion is that patients over the age of 80 who received their survey login codes on paper are the least responsive and underrepresented subgroup of the sample. In the analysis of the response time using Poisson regression, the conclusion is that the notification channel has the most significant impact on response rate. / Cancer är en mycket utbredd sjukdom världen över och kräver hundratals liv varje år. Inom cancerforskningen är det vanligt att genomföra undersökningar där patienter ombeds att självrapportera och bedöma sina symtom och övergripande hälsa. I sådana undersökningar är det avgörande att patienterna svarar snabbt på enkäter för att undvika minnesbias och för att få fram en representativ patientgrupp och undvika snedvriden urvalsprocess. Syftet med denna rapport är att undersöka faktorer som påverkar svarsfrekvensen och svarstiden genom att använda logistisk regression och Poisson-regression. Studien fokuserar på en dataset av patienter med tjocktarmscancer, där svarsfrekvensen hos patienter med bukspottkörtelcancer används som referens. Genom att analysera variabler som kön, ålder, bostadsort och metod för undersökningsmeddelande dras slutsatsen att patienter över 80 år som fick sina inloggningskoder på papper är den minst responsiva och mest underrepresenterade undergruppen av urvalet. I analysen av svarstiden med hjälp av Poisson-regression dras slutsatsen att undersökningskanalen har den största påverkan på svarsfrekvensen.

[pt] O objetivo da dissertação é analisar e comparar os fatores determinantes das inovações ambientais geradas pelas empresas brasileiras, segundo padrões setoriais de mudança tecnológica, tendo como fonte de dados os indicadores da Pesquisa Nacional de Inovação (Pintec) realizada pelo Instituto Brasileiro de Geografia e Estatística (IBGE). A pesquisa pode ser considerada descritiva e aplicada. A metodologia adotada compreendeu pesquisa bibliográfica sobre inovação, padrões setoriais de inovação; classificações tecnológicas e estratégias de baixo carbono, destacando-se a importância das inovações ambientais e a contribuição de estudos empíricos internacionais e nacionais sobre determinantes desse tipo de inovação; pesquisa documental referente à Classificação CNAE e à Pintec 2014, ambas publicadas pelo IBGE; análise de conteúdo para classificar as atividades econômicas das empresas respondentes da Pintec 2014, segundo os padrões setoriais de mudança tecnológica da taxonomia proposta por Pavitt; elaboração de plano tabular referente às questões da pesquisa para solicitação dos dados ao IBGE; recebimento e formatação dos dados da Pintec 2014; aplicação do modelo econométrico logit para análise dos determinantes de inovações ambientais por padrão setorial; interpretação e discussão dos resultados. A utilização de indicadores da Pintec 2014 para analisar os fatores determinantes da geração desse tipo de inovação e a associação desses indicadores aos padrões setoriais propostos por Pavitt conferem à pesquisa um caráter inovador, uma vez que os estudos anteriores sobre inovações ambientais não exploraram essa abordagem metodológica. Na esfera governamental, os resultados gerados (por padrão setorial) serão relevantes para a formulação de políticas públicas de inovação mais consistentes e bem estruturadas. / [en] This dissertation aims to analyze and compare the determinants of environmental innovations generated by Brazilian companies, according to sectoral patterns of technological change, using data from the National Innovation Survey (Pintec) published by the National Institute of Geography and Statistics (IBGE). The research can be considered descriptive and applied. The methodology included bibliographical research on innovation, sectoral patterns of technical change; technological classifications and low carbon corporate strategies, highlighting the importance of environmental innovations for achieving their targets; the contribution of previous empirical studies on the determinants of environmental innovations; documentary research concerning the CNAE Classification and the Pintec 2014, both published by IBGE; content analysis to classify the economic activities of respondent companies of Pintec 2014, according to the sectoral patterns of technological change, as proposed by Pavitt; elaboration of a tabular plan aligned to the research questions for requesting data to IBGE; data collection; application of the logit econometric model to analyze and compare the determinants of environmental innovations by sectoral pattern; interpretation and discussion of results. The use of indicators from Pintec 2014 to analyze and compare the determinants of this type of innovation and the association of these indicators with the sectoral patterns proposed by Pavitt give the research an innovative character, since previous studies on environmental innovation did not explore this methodological approach. At the governmental level, the results generated (by sectoral pattern of technical change) will be relevant for the formulation of more consistent and well-structured public policies concerning environmental innovation.

[pt] O objetivo da dissertação é analisar a influência de fatores de gestão da inovação, particularmente cooperação interorganizacional e uso de informação de diferentes fontes, sobre a percepção dos problemas e obstáculos enfrentados pelas pequenas e médias empresas (PMEs) inovadoras da indústria de transformação no Brasil, ao longo de suas atividades inovativas. Realizou-se esta análise segundo três níveis de intensidade tecnológica dos setores em que as PMEs atuam e duas faixas de pessoal alocado (pequenas e médias empresas). A pesquisa pode ser considerada descritiva e aplicada. A metodologia adotada compreendeu pesquisa bibliográfica sobre inovação; classificações tecnológicas, destacando-se a classificação de intensidade tecnológica proposta pela Organização para a Cooperação e Desenvolvimento Econômico (OCDE); análise comparada dos estudos empíricos internacionais e nacionais sobre problemas e obstáculos enfrentados por PMEs; pesquisa documental referente à Classificação CNAE e à Pesquisa Nacional de Inovação (Pintec), ambas as publicações do Instituto Brasileiro de Geografia e Estatística (IBGE); análise de conteúdo para classificar as atividades econômicas das PMEs respondentes da Pintec 2014, segundo três níveis de intensidade tecnológica dos setores em que atuam e duas faixas de pessoal alocado; solicitação dos microdados ao IBGE; desenvolvimento de modelos de regressão logística para seis agrupamentos de PMEs, classificadas por intensidade tecnológica setorial e por faixa de pessoal ocupado; interpretação e discussão dos resultados. A partir dos resultados do estudo empírico, conclui-se que as PMEs podem ampliar de forma significativa seu entendimento sobre a criticidade dos problemas e obstáculos à inovação à medida que se envolvem em atividades de PDeI, especialmente em modelos de inovação aberta. / [en] The dissertation aims to analyze the influence of innovation management factors, particularly inter-organizational cooperation and the use of information from different sources, on the perception of the problems and obstacles to innovation faced by small and medium-sized enterprises (SMEs) of the manufacturing industry in Brazil. This analysis was performed according to three levels of technological intensity of SMEs and firm size (small and medium enterprises). The research can be considered descriptive and applied. The methodology adopted comprised bibliographic research on innovation; technological classifications, highlighting the classification proposed by the Organization for Economic Cooperation and Development (OECD) for technological intensity of manufacturing sectors; comparative analysis of empirical studies on problems and obstacles faced by SMEs; documentary analysis focusing on the National Classification of Economic Activities (CNAE, acronym in Portuguese) and the National Innovation Survey (Pintec), both publications of the Brazilian Institute of Geography and Statistics (IBGE); content analysis to classify the economic activities of the respondent SMEs of Pintec 2014, according to three levels of technological intensity of the sectors in which they operate and two ranges of allocated personnel; request of microdata to IBGE; development of logistic regression models for six groups of SMEs; interpretation and discussion of the results innovation. From the results of the empirical study, the main conclusion is that SMEs can significantly broaden their understanding of the criticality of problems and obstacles to innovation as they engage in RandD activities, especially in open innovation models.

This paper aims to determine the value of the product based on the mathematical concept of Differential Privacy, by assessing the value of the business opportunities it enables and the value of the possible GDPR-fines it prevents. To delimit the scope of the research the analysis will focus on what the value of personal data is for companies within the mobility sector. Mobility is a cross-industrial sector consisting of companies within connectivity-technology, transportation, and automotive. The method used to assess the final value of anonymizing personal data, such as consumer data, using a DP-solution (meaning, an implementation of the theory) has consisted of both quantitative and qualitative analysis. The quantitative analysis aims to assess the ‘Cost of Risk’ for mobility companies that are exposed to personal integrity regulation due to data processing. To further conclude the true cost of the financial impact caused by getting fined for infringing on privacy regulation because of unlawful data processing is done through a complementary qualitative assessment. Lastly, the 'Opportunity Cost', or rather the cost of missed financial opportunities, is determined qualitatively for a case study company within Sweden’s mobility ecosystem to conclude the overall value of a DP-solution for a specific company. The final product of this research paper is to provide a framework assessing the total value, for specifically companies in the mobility sector, of implementing differential privacy solutions. / Syftet med denna uppsats är att fastställa värdet av anonymisering baserat på det matematiska konceptet Differential Privacy, genom att bedöma värdet av de affärsmöjligheter det skapar, samt värdet av de möjliga GDPR- böter det förhindrar. För att avgränsa studiens omfattning består analysen endast av att uppskatta dessa värden för företag inom mobilitetssektorn. Mobilitetssektorn är en tvärindustriell sektor som består av företag inom uppkoppling-, transport- och bilindustrin. Metoden som använts för att ta fram det slutliga värdet av att anonymisera persondata genom en differential privacy lösning, består både av en kvantitativ och en kvalitativ analys. Målet med den kvantitativa analysen är att estimera kostnadsrisken för företag inom mobilitetssektorn som exponeras mot GDPR-böter med avseende på dess datahantering. För att vidare ta reda på den totala finansiella inverkan av sådana böter, kompletteras analysen av en kvalitativ studie, som delvis omfattas av de finansiella möjligheterna ett företag går miste om i en sådan situation. Den kvalitativa analysen består också av en fallstudie av ett svenskt företag inom mobilitetssektorn, med målet att estimera värdet av de affärsmöjligheter som uppstår med hjälp av anonymisering av data. Slutligen är målet med denna uppsats att förse läsaren med att ramverk för att estimera det totala värdet av att implementera differential privacy lösningar i företag inom mobilitetssektorn.

The aim of this thesis is to develop and explore models in, and related to, the sufficient cause framework, and additive interaction. Additive interaction is closely connected with public health interventions and can be used to make inferences about the sufficient causes in order to find the mechanisms behind an outcome, for instance a disease. In paper A we extend the additive interaction, and interventions, to include continuous exposures. We show that there does not exist a model that does not lead to inconsistent conclusions about the interaction. The sufficient cause framework can also be expressed using Boolean functions, which is expanded upon in paper B. In this paper we define a new model based on the multifactor potential outcome model (MFPO) and independence of causal influence models (ICI). In paper C we discuss the modeling and estimation of additive interaction in relation to if the exposures are harmful or protective conditioned on some other exposure. If there is uncertainty about the effects direction there can be errors in the testing of the interaction effect. / Målet med denna avhandling är att utveckla, och utforska modeller i det så kallade sufficent cause ramverket, och additiv interaktion. Additiv interaktion är nära kopplat till interventioner inom epidemiology och sociologi, men kan också användas för statistiska tester för sufficient causes för att förstå mekanimser bakom ett utfall, tex en sjukdom. I artikel A så expanderar vi modellen för additiv interaktion och interventioner till att också inkludera kontinuerliga variabler. Vi visar att det inte finns någon modell som inte leder till motsägelser i slutsatsen om interaktionen. Sufficient cause ramverket kan också utryckas via Boolska funktioner, vilket byggs vidare på i artikel B. I den artikeln definerar vi en modell baserad på mutltifactor potential outcome modellen (MFPO) och independence of causal influence modellen (ICI). I artikel C diskuterar vi modelleringen och estimering av additiv interaktion i relation till om variablerna har skadlig eller skyddande effekt betingat på någon annan variabel. Om det finns osäkerhet kring en effekts riktning så kan det leda till fel i testerna för den additiva interaktionen. / <p>Examinator: Professor Henrik Hult, Matematik, KTH</p>

Depression, intertwined with sleep deprivation and self-esteem, presents a significant challenge to mental health worldwide. The research shown in this paper employs advanced statistical methodologies to unravel the complex interactions among these factors. Through log-linear homogeneous association, multinomial logistic regression, and generalized linear models, the study scrutinizes large datasets to uncover nuanced patterns and relationships. By elucidating how depression, sleep disturbances, and self-esteem intersect, the research aims to deepen understanding of mental health phenomena. The study clarifies the relationship between these variables and explores reasons for prioritizing depression research. It evaluates how statistical models, such as log-linear, multinomial logistic regression, and generalized linear models, shed light on their intricate dynamics. Findings offer insights into risk and protective factors associated with these variables, guiding tailored interventions for individuals in psychological distress. Additionally, policymakers can utilize these insights to develop comprehensive strategies promoting mental health and well-being at a societal level.

Multiple studies have documented declines of forest breeding birds in the eastern United States, but the temporal and spatial scales of most studies limit inference regarding large scale bird-habitat trends. A potential solution to this challenge is integrating existing long-term datasets such as the U.S. Forest Service Forest Inventory and Analysis (FIA) program and U.S. Geological Survey Breeding Bird Survey (BBS) that span large geographic regions. The purposes of this study were to determine if FIA metrics can be related to BBS population indices at multiple spatial and temporal scales and to develop predictive models from these relationships that identify forest conditions favorable to forest songbirds. I accumulated annual route-level BBS data for 4 species guilds (canopy nesting, ground and shrub nesting, cavity nesting, early successional), each containing a minimum of five bird species, from 1966-2004. I developed 41 forest variables describing forest structure at the county level using FIA data from for the 2000 inventory cycle within 5 physiographic regions in 14 states (AL, GA, IL, IN, KY, MD, NC, NY, OH, PA, SC, TN, VA, and WV). I examine spatial relationships between the BBS and FIA data at 3 hierarchical scales: 1) individual BBS routes, 2) FIA units, and 3) and physiographic sections. At the BBS route scale, I buffered each BBS route with a 100m, 1km, and 10km buffer, intersected these buffers with the county boundaries, and developed a weighted average for each forest variable within each buffer, with the weight being a function of the percent of area each county had within a given buffer. I calculated 28 variables describing landscape structure from 1992 NLCD imagery using Fragstats within each buffer size. I developed predictive models relating spatial variations in bird occupancy and abundance to changes in forest and landscape structure using logistic regression and classification and regression trees (CART). Models were developed for each of the 3 buffer sizes, and I pooled the variables selected for the individual models and used them to develop multiscale models with the BBS route still serving as the sample unit. At the FIA unit and physiographic section scales I calculated average abundance/route for each bird species within each FIA unit and physiographic section and extrapolated the plot-level FIA variables to the FIA unit and physiographic section levels. Landscape variables were recalculated within each unit and section using NCLD imagery resampled to a 400 m pixel size. I used regression trees (FIA unit scale) and general linear models (GLM, physiographic section scale) to relate spatial variations in bird abundance to the forest and landscape variables. I examined temporal relationships between the BBS and FIA data between 1966 and 2000. I developed 13 forest variables from statistical summary reports for 4 FIA inventory cycles (1965, 1975, 1989, and 2000) within NY, PA, MD, and WV. I used linear interpolation to estimate annual values of each FIA variable between successive inventory cycles and GLMs to relate annual variations in bird abundance to the forest variables. At the BBS route scale, the CART models accounted for > 50% of the variation in bird presence-absence and abundance. The logistic regression models had sensitivity and specificity rates > 0.50. By incorporating the variables selected for the models developed within each buffer (100m, 1km, and 10km) around the BBS routes into a multiscale model, I was able to further improve the performance of many of the models and gain additional insight regarding the contribution of multiscale influences on bird-habitat relationships. The majority of the best CART models tended to be the multiscale models, and many of the multiscale logistic models had greater sensitivity and specificity than their single-scale counter parts. The relatively fine resolution and extensive coverage of the BBS, FIA, and NLCD datasets coupled with the overlapping multiscale approach of these analyses allowed me to incorporate levels of variation in both habitat and bird occurrence and abundance into my models that likely represented a more comprehensive range of ecological variability in the bird-habitat relationships relative to studies conducted at smaller scales and/or using data at coarser resolutions. At the FIA unit and physiographic section scales, the regression trees accounted for an average of 54.1% of the variability in bird abundance among FIA units, and the GLMs accounted for an average of 66.3% of the variability among physiographic sections. However, increasing the observational and analytical scale to the FIA unit and physiographic section decreased the measurement resolution of the bird abundance and landscape variables. This limits the applicability and interpretive strength of the models developed at these scales, but they may serve as indices to those habitat components exerting the greatest influences on bird abundance at these broader scales. The GLMs relating average annual bird abundance to annual estimates of forest variables developed using statistical report data from the 1965, 1975, 1989, and 2000 FIA inventories explained an average of 62.0% of the variability in annual bird abundance estimates. However, these relationships were a function of both the general habitat characteristics and the trends in bird abundance specific to the 4-state region (MD, NY, PA, and WV) used for these analyses and may not be applicable to other states or regions. The small suite of variables available from the FIA statistical reports and multicollinearity among all forest variables further limited the applicability of these models. As with those developed at the FIA unit and physiographic sections scales, these models may serve as general indices to the habitat components exerting the greatest influences on bird abundance trends through time at regional scales. These results demonstrate that forest variables developed from the FIA, in conjunction with landscape variables, can explain variations in occupancy and abundance estimated from BBS data for forest bird species with a variety of habitat requirements across spatial and temporal scales. / Ph. D.