Background: The spirometric reference values are of great importance for diagnosis and treatment of lung diseases. At present, there are no spirometric reference values for First Nations children and adolescents living in Canada. Objectives: The objectives of the present study were (1) to identify the flexible and efficient statistical method to derive lung function reference equations that can be used to obtain the predicted values and Lower Limit of Normal (LLN) for lung function in children and adolescents, and (2) to obtain prediction equations for FVC, FEV1 and FEV1=FVC for First Nations children and adolescents living in rural Saskatchewan, Canada. Methods: Spirometric results from a prospective cohort study, "First Nations Lung Health Project" were used to identify 130 healthy non-smoking children and adolescents. The predicted values and LLN of spirometric indices [Forced Vital Capacity (FVC), Forced Expiratory Volume at one second (FEV1) and FEV1 and FVC ratio (FEV1=FVC)] were calculated for school-going children and adolescents ages 6-17 years. The subjects participating in the study were from two Cree First Nations on-reserve communities located in rural Saskatchewan, Canada. All lung function values were reviewed by a respirologist for acceptability of the test. Following an extensive literature review, the Generalized Additive Models for Location, Scale and Shape (GAMLSS) was identified as a flexible statistical tool to model the lung function variables. The lung function indices were assumed to follow a Box-Cox-Cole-Green (BCCG) distribution with median, , coe ffcient of variation and skewness . Akaike Information Criteria (AIC) approach was used to obtain the reference models. The LLN was calculated by taking the fifth percentile of the prediction equations of the lung function variables. The above approach is recommended for the prediction of lung function of multi-ethnic people aged 3-95 years from different ethnic groups by the Global Lung Function Initiative (GLI). Results: Significant differences were observed in lung function (FVC, FEV1 and FEV1=FVC) and anthropometric measurements between both boys and girls. Therefore, fitting separate equations for both sexes are justified. In GLI, polynomial bases of order 6-7 were used for modeling the meadian, coefficient of variation and skewness . In this study, lower order polynomial bases (up to order 4) were enough to obtain the reference models. In GLI, the polynomial bases were divided by 100 to let it lie within 0 to 1. In this study, the polynomials were divided by 20 to lie these between 0 and 1. The predicted values of FVC was higher than the values for FEV1 in both boys and girls. Therefore the values of FEV1=FVC ratios is less than 100% in this population. In girls, the difference between the curves of FVC and FEV1 was smaller compared to boys. Thus, the total volume of air for girls during exhalation are close to the volume of air exhaled at the first second. The estimated curves showed that the models fitted the lung function data reasonably well. Conclusions: The results in this study showed that the optimum model for the prediction of lung function were almost similar to the ones used by GLI for the prediction of lung function of all-age multi-ethnic populations.The predicted values and LLN values of the lung function variables reported in this study can be recommended to health-care providers for the use in diagnosis respiratory diseases in First Nations children and adolescents in rural Saskatchewan. Small sample (n < 150) was a limitation of this study. This study limitation can be overcome by including more individuals from the follow-up study, which will be conducted in 2016.

The cause and effect paradigm underlying medical research has led to an enhanced etiological understanding of many diseases and the development of many lifesaving drugs, but the paradigm does not always include an understanding of the pathways involved. Causal mediation analysis extends the cause and effect relationship to the cause and effect through a mediator, an intermediate variable on the causal pathway. The total effect of an exposure on an outcome is decomposed into two parts: 1) the indirect effect of the exposure on the outcome through the mediator and 2) the direct effect of the exposure on the outcome through all other pathways. In this dissertation, I describe various counterfactual causal mediation frameworks with identifiability assumptions that all lead to the Mediation Formula. The indirect and direct effects can be estimated from observable data using a semi-parametric algorithm derived from the Mediation Formula that I generalize to different types of mediators and outcomes. With an increased interest in causal mediation analysis, thoughtful consideration is necessary in the application of the Mediation Formula to real-world data challenges. Here, I consider three motivating causal mediation questions in the areas of HIV curative research and cardio-respiratory fitness. HIV curative treatments typically target the viral reservoir, cells infected with latent HIV. Quantifying the effect of an HIV curative treatment on viral rebound over a set time horizon mediated by reductions in the viral reservoir can inform future directions for improving curative treatments. In cardiorespiratory fitness research, metabolites, molecules involved with cellular respiration, are believed to mediate the effect of physical activity on cardiorespiratory fitness. I propose three novel adaptations to the semi-parametric estimation algorithm to address three data challenges: 1) Numerical integration and optimization of the observed data likelihood for mediators with an assay lower limit (left-censored mediators); 2) Pseudo-value approach for time-to-event outcomes on a restricted mean survival time scale; 3) Elastic net regression for high-dimensional mediators. My novel approaches provide estimation frameworks that can be applied to a broad spectrum of research questions. I provide simulation studies to assess the properties of the estimators and applications of the methodologies to the motivating data. / 2025-06-16T00:00:00Z

<p dir="ltr">This thesis presents two studies in search for violation of lepton flavor universality as predicted by the Standard Model. The first searches for signs of the violation by studying beyond the Standard Model (BSM) physics models involving same flavor and opposite sign dilepton pair and bottom quarks as final states. This study was done using the dataset collected during years of 2016, 2017 and 2018, with center of mass energy $\sqrt{s} = 13$ TeV and integrated luminosity of 138 $fb^-1$. In the study, scale factors were derived in order to correct deviations between simulation and real life data, specifically for high transverse momentum muons and top\&anti-top quark background. Furthermore, lower limits of energy scale were calculated leading to exclusion of the BSM models with energy scale values lower than that of the calculated value.</p><p dir="ltr">The second study also searches for of the lepton flavor universality violation, but in the specific decay of a tauon into three muons ($\tau \rightarrow 3\mu$). In the study, graph based neural network model (GNN) designed to classify $\tau \rightarrow 3\mu$ events at the CMS detector was converted to high level synthesis (HLS) code, so that the GNN could be coded into a custom hardware such as field programmable gate arrays (FPGA) for deployment. Moreover, techniques such as pruning and quantization were applied in an attempt to make the GNN more light weight, due to strict requirements of FPGA.</p>