Forest quantification methods have evolved from a simple graphical approach to complex regression models with stochastic structural components. Currently, mixed effects models methodology is receiving attention in the forestry literature. However, the review work (Paper I) indicates a tendency to overlook appropriate covariance structures in the NLME modeling process. A nonlinear mixed effects modeling process is demonstrated in Paper II using Cupressus lustanica tree merchantable volume data and compared several models with and without covariance structures. For simplicity and clarity of the nonlinear mixed effects modeling, four phases of modeling were introduced. The nonlinear mixed effects model for C. lustanica tree merchantable volume with the covariance structures for both the random effects and within group errors has shown a significant improvement over the model with simplified covariance matrix. However, this statistical significance has little to explain in the prediction performance of the model. In Paper III, using several performance indicator statistics, tree taper models were compared in an effort to propose the best model for the forest management and planning purpose of the C. lustanica plantations. Kozak's (1988) tree taper model was found to be the best for estimating C. lustanica taper profile. Based on the Kozak (1988) tree taper model, a Ds optimal experimental design study is carried out in Paper IV. In this study, a Ds-optimal (sub) replication free design is suggested for the Kozak (1988) tree taper model.

En dépit d’épidémies répétées, il n’existe pas à ce jour de thérapeutique ayant démontré son efficacité dans la maladie à virus Ebola. Sur la base d’expérimentations réalisées chez la souris et le macaque dans le cadre du consortium Reaction!, l’objectif de cette thèse visait à caractériser l’effet d’une molécule antivirale, le favipiravir, via l’implémentation de modèles mathématiques mécanistiques de l’infection et de la réponse immunitaire associée. L’approche utilisée pour construire ces modèles et en estimer les paramètres reposait sur les modèles non linéaires à effets mixtes. Un premier travail a permis d’explorer la relation concentration-effet sur la charge virale plasmatique chez la souris. Le second projet a conduit à caractériser la pharmacocinétique non linéaire dose et temps dépendante du favipiravir chez le macaque, en vue d’identifier les schémas posologiques pertinents pour la réalisation des études d’efficacité chez l’animal infecté. Au décours de leur réalisation, l’intégration des données virologiques et immunitaires générées au sein d’un modèle conjoint a permis de caractériser un effet modéré du favipiravir sur la réplication virale, mais suffisant pour limiter le développement d’une réaction inflammatoire délétère, et ainsi améliorer le taux de survie des animaux traités. Les simulations réalisées avec ce modèle ont pu souligner l’impact déterminant du délai d’initiation du traitement sur la survie. Ces résultats incitent à la poursuite de l’évaluation clinique du favipiravir, en favorisant des essais de prophylaxie ou post exposition. Enfin, un dernier travail a démontré l’absence de potentialisation du favipiravir par la ribavirine dans Ebola. / In spite of recurrent outbreaks, no therapeutics with demonstrated clinical efficacy are available in Ebola virus disease. Based on experimentations performed by Reaction! Consortium in mice and macaques, this thesis aimed to characterize the effect of an antiviral drug, favipiravir, using mechanistic mathematical models of the infection and associated immune response. The approach to build models and estimate parameters relied on nonlinear mixed effect models. The first project of this thesis explored the concentration-effect relationship on the viremia in mice. Then, a second project allowed to characterize the pharmacokinetics of favipiravir in macaques, underlying dose and time non linearity, and to identify relevant dosing regimen for efficacy experiments in infected animals. Once these experiments completed, the integration of the virological and immunological data into a mechanistic joint model shed light on the effect of favipiravir. The moderate inhibition of the viral replication resulting from the favipiravir plasma concentrations was enough to limit the development of a deleterious inflammatory response, and thus improve the survival rate of treated macaques. Simulations performed with this model underlined the crucial impact of the treatment initiation delay on survival. These results encourage the pursuit of the clinical evaluation of favipiravir in prophylaxis or post exposure trials. Finally, a last project demonstrated the lack of benefit of ribavirin addition to favipiravir in Ebola virus disease.

Background : Studies of self-rated oral health are always done at either the individual level or the aggregate level. Partitioning individual and neighbourhood sources of variation also enables explorations of the influences of people’s social context on their self-rated oral health. Objective : The main objective of the study was to examine the influence of the social context in which people live on their self-rating of their oral health, independent of individual indicators of good oral health. Method : This study used a secondary analysis of data on a nationally representative sample of 2 907 South African adults (aged ≥ 16 years) who had participated in the 2007 annual South African Social Attitude Survey (SASAS). The 2007 SASAS used a multi-stage probability sampling strategy, with census enumeration areas as the primary sampling unit. Using an interviewer-administered questionnaire, the information obtained included socio-demographic data, the respondents’ level of trust in people (a proxy measure for social capital), oral health behaviours and self-rated oral health. Using the 2005 General Household Survey (GHS) (persons’ n=107 987; households’ n=28 129), the living environment characteristics of participants of the SASAS were obtained, including sources of water and energy supply and household cell phone ownership as a proxy measure for social networking. A mixed-effects model was then constructed to determine factors associated with a self-rating of oral health as ‘very good/good’. Results : Of the respondents, 51.7% were female. Among the respondents, 76.3% self-rated their oral health as good. There was a significant gender modifying effect, thus analyses was stratified by gender. The odds of self-rating oral health as good was significantly higher only among females living in areas with higher household cell phone ownership density, even after controlling for potential confounders. At the individual level, trust was positively associated with good self-rated oral health only among males, and higher social ranking in the society was positively associated with good self-rated oral health only among females. Overall, 55% of the total variance in self-rated oral health was explained by factors operating at the individual level, whereas 18% of the total variance was explained by factors operating at the community level. Self-report of recent oral health problems such as toothache and oral malodour were significantly associated with lower odds of self-rating their oral health as good, as was with reporting less frequent brushing. Conclusion : Good self-rated oral health may be positively associated with indicators of higher levels of social capital both at the level of the individual and the community and with less physical impairments of oral functioning. Furthermore, the findings indicate that unlike men’s oral health ratings, women’s oral health ratings are more likely to be influenced by women’s social relationships with others in the society. Copyright / Dissertation (MSc)--University of Pretoria, 2011. / School of Health Systems and Public Health (SHSPH) / Unrestricted

Longitudinal assessments are crucial in evaluating the disease state and trajectory in patients of neurodegenerative diseases. Neuropsychological outcomes measured over time often have a non-linear trajectory with autocorrelated residuals and skewed distributions. Due to these issues, statistical analysis and interpretation involving longitudinal cognitive outcomes can be a difficult and controversial task, thus hindering most convenient transformations (e.g. logarithmic) to avoid the assumption violations of common statistical modelling techniques. We propose the Adjusted Local Linear Trend (ALLT) model, an extended state space model in lieu of the commonly-used linear mixed-effects model (LMEM) in modeling longitudinal neuropsychological outcomes. Our contributed model has the capability to utilize information from the stochasticity of the data while accounting for subject-specific trajectories with the inclusion of covariates and unequally-spaced time intervals. The first step of model fitting involves a likelihood maximization step to estimate the unknown variances in the model before parsing these values into the Kalman Filter and Kalman Smoother recursive algorithms. Results from simulation studies showed that the ALLT model is able to attain lower bias, lower standard errors and high power, particularly in short longitudinal studies with equally-spaced time intervals, as compared to the LMEM. The ALLT model also outperforms the LMEM when data is missing completely at random (MCAR), missing at random (MAR) and, in certain cases, even in data with missing not at random (MNAR). In terms of model selection, likelihood-based inference is applicable for the ALLT model. Although a Chi-Square distribution with k degrees of freedom, where k is the number of parameter lost during estimation, was not the asymptotic distribution in the case of ALLT, we were able to derive an asymptotic distribution approximation of the likelihood ratio test statistics using the power transformation method for the utility of a Gaussian distribution to facilitate model selections for ALLT. In light of these findings, we believe that our proposed model will shed light into longitudinal data analysis not only in the neuropsychological data realm but also on a broader scale for statistical analysis of longitudinal data. / 2023-10-05T00:00:00Z

Práce se zabývá longitudinálními daty - měřeními, která jsou prová- děna opakovaně na stejných subjektech. Popisuje r·zné typy model·, které jsou vhodné pro jejich analýzu. Postupuje od nejjednodušších lineárních model· s pevnými nebo náhodnými efekty, přes lineární a nelineární modely se smíšenými efekty, až ke zobecněným lineárním model·m a generalized estimating equati- ons (GEE). Vždy je uveden tvar modelu a zp·sob odhadu parametr·. Jednotlivé modely jsou také porovnávány mezi sebou. Teoretické poznatky jsou doplněny aplikacemi na reálná data. Pomocí lineárních model· analyzujeme data o výrobě v USA, nelineární modely využijeme k vysvětlení závislosti koncentrace léčiva v krvi na čase a GEE aplikujeme na data týkající se dýchacích potíží u dětí. 1

För att möjliggöra interaktion med den stora mängd datorenheter som dyker upp i vår vardagkrävs nya gränssnitt och ett nytt synsätt på teknologi. Reflexiv interaktion, en specifik del avperifer interaktion, ämnar att skapa interaktioner som sker under en bråkdel av en sekundmed ett sekundärt system, vilket skapar bättre förutsättningar för ett effektivt arbete ochminskar risken för misstag. Kognitiv belastning är centralt inom perifer interaktion och ännuviktigare i reflexiv interaktion, det saknas dock undersökningar där den kognitivabelastningen mäts och undersöks för perifera eller reflexiva interaktioner.Teorin om kognitiv belastning är väl utforskad inom forskningsområdet instruktionsdesign,och delar av den kunskap som skapats inom instruktionsdesign har applicerats inommänniska-datorinteraktion. Det finns dock fortfarande aspekter av kognitiv belastning somundersökts i instruktionsdesign men är outforskade inom människa-datorinteraktion.En studie med 19 deltagare har undersökt den kognitiva belastningen för en central del ireflexiv interaktion: notifikationer. Studiens resultat visar på att skillnaden i kognitivbelastning mellan ljudliga och visuella notifikationer är väldigt liten.

Tuberculosis is one the leading causes of death globally and was before the COVID-19 pandemic the leading cause of death from a single infectious agent. Developing active tuberculosis is life threatening and therefore is the rise of drug-resistant tuberculosis alarming as this risk causing current treatments to become ineffective. Linezolid is a promising drug for treatment of drug-resistant pulmonary tuberculosis, but the effect of linezolid treatment for pulmonary tuberculosis subjects is still not understood well enough and the World Health Organization has requested this knowledge gap to be filled. In this project we support the closing of this knowledge gap by describing the pharmacokinetics of linezolid for treatment of pulmonary tuberculosis using data collected from a phase two clinical trial in a South African population. This was done by creating a pop-PK model and resulted in the PK of linezolid in pulmonary tuberculosis patients from South Africa was best described using a one-compartment model, with first-order absorption process preceded by a series of transit compartments and saturable elimination. However, the diagnostics of the model still show that there are room for improvements and future work is necessary to further optimize the model.

Anticipated climate change and increasing wood demand require dependable diameter growth models for adaptive forest management. We used a mixed-effects modeling approach with Forest Inventory and Analysis (FIA) data to fit diameter growth models for loblolly pine, other softwood species (slash pine, shortleaf pine, and longleaf pine), sweetgum, and other hardwood (southern red oak, red maple, and water oak) species. Climatic variables coupled with individual tree attributes and competition factors improved climate insensitive models. Growth of loblolly pine and sweetgum was positively correlated with mean temperature of the coldest month. Mean temperature of the warmest month negatively influenced diameter growth of loblolly pine and other hardwood species. Growing season precipitation and summer precipitation balance had negative effects on the growth of softwood and hardwood species, respectively. Inclusion of FIA plot as random effect improved model fit statistics and residual distribution of climate sensitive models. These findings will be useful to managers for recalibrating diameter growth models resulting in improved biomass yield and volume estimates that will better inform decisions.

It is well established in the literature that children with developmental coordination disorder (DCD) are more likely to be physically inactive, have unhealthy weight, and report lower perceptions of self-worth than typically developing (TD) children. Physical inactivity, overweight/obesity and low self-worth are important risk factors for many physical and psychological health conditions. The interrelationships among these factors, however, have yet to be explored in children with DCD. There is limited information on change in body composition measures and self-worth over time in children with DCD, the effect of physical activity (PA) on body composition, and whether the combined negative influence of having both DCD and obesity result in poorer conceptions of self-worth. In this dissertation, I present a series of studies that explore the connections among these factors using longitudinal, population-based data on a large cohort of children with and without poor motor coordination. The first study, presented in Chapter 2, describes the results of change in BMI and waist circumference (WC) in children with probable DCD (pDCD) and TD children over a five-year time period, and the effects of sex and PA on this relationship. Chapter 3 describes the results of the relationship between body fat, pDCD, and PA after addressing the measurement- related limitations of the study reported in Chapter 2. Chapter 4 describes the results of self-worth in children with pDCD and overweight/obesity, only pDCD, only overweight/obesity, and the control group at baseline as well as change over time. Collectively, the results show that children with pDCD have a consistently higher BMI, WC, and body fat than TD children. BMI and WC increases over time in children with pDCD; specifically boys with pDCD show a much accelerated increase in these measures. Scores of body composition measures increase with decrease in self-reported and objectively measured PA, but participation in PA does not explain why children with pDCD are more likely to have excess weight gain. Finally, children with both pDCD and overweight/obesity and children with either of these conditions alone report lower self- worth than the control group, and the change in self-worth between groups remains constant over time. / Dissertation / Doctor of Philosophy (PhD)

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