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<p>Subjects enrolled in a clinical trial may experience a competing risk event which alters the risk of the primary event of interest. This differs from when subject information is censored, which is non-informative. In order to calculate the cumulative incidence function (CIF) for the event of interest, competing risks and censoring must be treated appropriately; otherwise estimates will be biased. There are two commonly used methods of calculating a confidence interval (CI) for the CIF for the event of interest which account for censoring and competing risk: the Kalbfleisch-Prentice (KP) method and the Counting Process (CP) method. The goal of this paper is to understand the variances associated with the two methods to improve our understanding of the CI. This will allow for appropriate estimation of the CIF CI for a single-arm cohort study that is currently being conducted. Previous work has failed to address this question because researchers typically focus on comparing two treatment arms using statistical tests that compare cause-specific hazard functions and do not require a CI for the CIF. The two methods were compared by calculating CIs for the CIF using data from a previous related study, using bootstrapping, and a simulation study with varying event rates and competing risk rates. The KP method usually estimated a larger CIF and variance than the CP method. When event rates were low (5%), the CP method is recommended as it yields more consistent results than the KP method. The CP method is recommended for the proposed study since event rates are expected to be moderate (5-10%).</p> / Master of Science (MS)

Network meta-analysis (NMA) synthesizes all available direct (head-to-head) and indirect evidence on the comparative effectiveness of at least three treatments and provides coherent estimates of their relative effects. Ranking probabilities are commonly used to summarize these estimates and provide comparative rankings of treatments. However, the reliability of ranking probabilities as summary measures has not been formally established and treatments are often ranked for each outcome separately. This thesis aims to address methodological gaps and limitations in current literature by providing alternative methods for evaluating the robustness of treatment ranks, establishing comparative rankings, and integrating ranking probabilities across multiple outcomes. These novel tools, addressing three specific objectives, are developed in three papers. The first paper presents a conceptual framework for quantifying the robustness of treatments ranks and for elucidating potential sources of lack of robustness. Cohen’s kappa is proposed for quantifying the agreement between two sets of ranks based on NMAs of the full data and a subset of the data. A leave one-study-out strategy was used to illustrate the framework with empirical data from published NMAs, where ranks based on the surface under the cumulative ranking curve (SUCRA) were considered. Recommendations for using this strategy to evaluate sensitivity or robustness to concerning evidence are given. When two or more cumulative ranking curves cross, treatments with large probabilities of ranking the best, second best, third best, etc. may rank worse than treatments with smaller corresponding probabilities based on SUCRA. This limitation of SUCRA is addressed in the second paper through the proposal of partial SUCRA (pSUCRA) as an alternative measure for ranking treatments. pSUCRA is adopted from the partial area under the receiver operating characteristic curve in diagnostic medicine and is derived to summarize relevant regions of the cumulative ranking curve. Knowledge users are often faced with the challenge of making sense of large volumes of NMA results presented across multiple outcomes. This may be further complicated if the comparative rankings on each outcome contradict each other, leading to subjective final decisions. The third paper addresses this limitation through a comprehensive methodological framework for integrating treatments’ ranking probabilities across multiple outcomes. The framework relies on the area inside spie charts representing treatments’ performances on all outcomes, while also incorporating the outcomes’ relative importance. This approach not only provides an objective measure of the comparative ranking of treatments across multiple outcomes, but also allows graphical presentation of the results, thereby facilitating straightforward interpretation. All contributions in this thesis provide objective means to improve the use of comparative treatment rankings in NMA. Further extensive evaluations of these tools are required to assess their validity in empirical and simulated networks of different size and sparseness. / Thesis / Doctor of Philosophy (PhD) / Decisions on how to best treat a patient should be informed by all relevant evidence comparing the benefits and harms of available options. Network meta-analysis (NMA) is a statistical method for combining evidence on at least three treatments and produces a coherent set of results. Nevertheless, NMA results are typically presented separately for each health outcome (e.g., length of hospital stay, mortality) and the volume of results can be overwhelming to a knowledge user. Moreover, the results can be contradictory across multiple outcomes. Statistics that facilitate the ranking of treatments may aid in easing this interpretative burden while limiting subjectivity. This thesis aims to address methodological gaps and limitations in current ranking approaches by providing alternative methods for evaluating the robustness of treatment ranks, establishing comparative rankings, and integrating ranking probabilities across multiple outcomes. These contributions provide objective means to improve the use of comparative treatment rankings in NMA.

With an increasing share of intermittent electricity production in the energy system, there is an increased need for energy storage. Because of electrochemical batteries’ ability of modularization, fast response and flexibility, grid connected energy storage will enable load balance and dispatching stored energy to optimize grid operations. Grid operation applications such as frequency regulations, peak- and time-shifting will enable saving otherwise curtailed renewable energy. The extraction of materials and the manufacturing of batteries are though energy intense processes themselves. Ligna Energy develops an organic battery, based on organic electronic polymers and biopolymers from the forest. These organic batteries are less energy dense, but do not contain conflicts material, require any strict, energy consuming production environment and can be burned as biofuels in the end of life. Standardize methods for life cycle assessment is a useful tool to determine the cumulative energy demand from extraction of material to end of life thermal conversion. Operation applications such as increase of self-consumption, energy time shift and frequency regulation show that the Ligna Energy organic battery deliver more energy to the grid through the specific operation, than demanded for manufacturing after 15, 9 respectively 1 year.

Elderly Black and Hispanic adults have poorer overall health, higher disability rates, and lower life expectancies than elderly Whites and other racial and ethnic minority group members. There are also sex differences in health, with women more likely to suffer from non-life threatening chronic conditions and men more likely to suffer from acute conditions. Health pathways, or the processes to good or poor health, are shaped by race, SES, and sex. This study focuses on the race and SES literature, framing race and SES inequalities within a cumulative advantage lens. Using Hierarchical Linear Modeling techniques to examine data from the Health and Retirement Survey, this study finds that there are racial differences in health through health problems, health insurance, and health care treatment, and that Black, Hispanic, and other racial and ethnic minority group members have worse self-reported health than Whites in old age. This study also finds evidence of cumulative advantage through friends in the neighborhood, and finds evidence of cumulative disadvantage through health problems and hospital and nursing home treatment. There are also cumulative disadvantages for women, who have more functional limitations in old age than their male counterparts, and these disadvantages grow over time. This study adds support to the race literature, by furthering understandings of race and SES as interconnected but not interchangeable systems of inequality. In lieu of the findings, this study provides implications for future research and ways to reduce racial health disparities in old age. / Ph. D.

Intensive mothering (IM) is increasingly being recognized as a dominant parenting discourse. IM, conceptualized as hyper-parenting ideals that place pressure on mothers to cultivate children's cognitive development, has also been demonstrated to have consequences for mothers' mental wellbeing. On the other hand, IM attitudes also appear to contribute to parenting strategies that can be considered beneficial for young children's developmental growth. Considering these complexities, the present research was grounded in a theoretical framework guided by ecological and risk and resilience theories to test a holistic model which positioned IM as having indirect associations with children's executive functioning (EF) through two pathways: positive parenting strategies and parenting stress. Contrary to the theoretical purposes of IM-informed parenting, IM did not contribute to better cognitive outcomes in 3–5-year-old children through positive parenting. Instead, IM indirectly contributed to higher reports of dysfunctions in children's EF through the mechanism of parenting stress. Further, a conditional process model advanced previous understandings of IM by illuminating the processes through which cumulative risk strengthened the associations between these core constructs. Based on the results presented in this research, IM ideology is argued to be a context of risk for families with an accumulation of contextual risk factors. / Doctor of Philosophy / This research study investigated how modern parenting beliefs, called "intensive mothering", related to mothers' experiences with parenting stress, parenting behaviors that are considered good for young children, and young children's developmental outcomes. Intensive mothering involves beliefs such as "children needs should come before the parents' needs" and "it is the mothers' job to make sure young children are intellectually stimulated as much as possible." While these ideas would seem like good things for young children, this study found that having such high standards for mothers parenting expectations create more stress in mothers which, consequently, was related to worse developmental outcomes for young children. If the families who participated in this research had a few characteristics that make it harder for families to thrive, like limited financial resources, then they seemed to report even more parenting stress and even worse outcomes for their children. These findings suggest that holding such high parenting expectations may unintentionally hurt mothers and their children.

The co-occurrence of anxiety disorders (ADs) and disruptive behavior disorders affects a substantial proportion of children and may cause significant impairment in functioning. Approximately 40% of clinic-referred youth with oppositional defiant disorder (ODD) meet criteria for an AD (Greene et al., 2002). In spite of the frequent co-occurrence of these disorders, there is little research examining the presence of AD in clinic-referred samples of youth with ODD. Thus, the purpose of the current study was to 1) examine the phenomenology of clinic-referred youth with ODD/AD as compared to youth with ODD alone, and 2) explore the role of cumulative family risk (CFR) in predicting level of impairment in youth with comorbid ODD/AD as compared to youth with ODD alone. There was mixed support for distinct clinical profiles among youth with ODD/AD as compared to youth with ODD alone: youth with ODD/AD had higher levels of anxiety, internalizing symptoms, and parent psychopathology whereas youth with ODD alone had higher levels of conduct problems, hyperactivity, and attention difficulties. However, there was little support for the role of CFR in predicting impairment in youth with ODD/AD. Future research should enlist a multi-informant, multi-contextual approach in examining the role of CFR in predicting impairment levels for youth with comorbid ODD/AD. / Ph. D.

Accelerated life tests (ALT) are appealing to practitioners seeking to maximize information gleaned from reliability studies, while navigating resource constraints due to time and specimen costs. A popular approach to accelerated life testing is to design test regimes such that experimental specimens are exposed to variable stress levels across time. Such ALT experiments allow the practitioner to observe lifetime behavior across various stress levels and infer product life at use conditions using a greater number of failures than would otherwise be observed with a constant stress experiment. The downside to accelerated life tests, however, particularly for those that utilize non-constant stress levels across time on test, is that the corresponding lifetime models are largely dependent upon assumptions pertaining to variant stress. Although these assumptions drive inference at product use conditions, little to no statistical methods exist for assessing their validity. One popular assumption that is prevalent in both literature and practice is the cumulative exposure model which assumes that, at a given time on test, specimen life is solely driven by the integrated stress history and that current lifetime behavior is path independent of the stress trajectory. This dissertation challenges such black box ALT modeling procedures and focuses on the cumulative exposure model in particular. For a simple strep-stress accelerated life test, using two constant stress levels across time on test, we propose a four-parameter Weibull lifetime model that utilizes a threshold parameter to account for the stress transition. To circumvent regularity conditions imposed by maximum likelihood procedures, we use median rank regression to fit and assess our lifetime model. We improve the model fit using a novel incorporation of desirability functions and ultimately evaluate our proposed methods using an extensive simulation study. Finally, we provide an illustrative example to highlight the implementation of our method, comparing it to a corresponding Bayesian analysis. / Ph. D.