The relationship between alcoholism and generalized anxiety disorder (GAD) has been discussed in two research areas: research on the prevalence of GAD in alcoholics, and the prevalence of alcoholism in individuals diagnosed with GAD. Studies indicate that between 6 to 26% of alcoholics have a current diagnosis of GAD, with a lifetime prevalence rate of up 51%. In the general population, 4% would currently receive a diagnosis of GAD, with a lifetime prevalence of 8%. This meta-analytic review of the empirical literature examines the relationship between GAD and alcoholism. The author used percentages to compare the results of various studies. The averaged results of these various studies suggested there is a 25% comorbidity rate of GAD and alcoholism. critical review of the studies examined in this review revealed substantial methodological errors. Based on a critical review of the research methodology in the studies cited, the author proposed further research.

The generalized Pareto distribution was introduced by Pickands (1975). Three methods of estimating the parameters of the generalized Pareto distribution were compared by Hosking and Wallis (1987) . The methods are maximum likelihood, method of moments and probability-weighted moments. An alternate method of estimation for the generalized Pareto distribution, based on least square regression of expected order statistics (REOS), is developed and evaluated in this thesis . A Monte Carlo comparison is made between this method and the estimating methods considered by Hosking and Wallis (1987). This method is shown to be generally superior to the maximum likelihood, method of moments and probability-weighted moments

Indiana University-Purdue University Indianapolis (IUPUI) / The two-part model (2PM) is the most widely applied modeling and estimation framework in empirical health economics. By design, the two-part model allows the process governing observation at zero to systematically differ from that which determines non-zero observations. The former is commonly referred to as the extensive margin (EM) and the latter is called the intensive margin (IM). The analytic focus of my dissertation is on the development of a general framework for specifying, estimating and drawing inference regarding causally interpretable (CI) effect parameters in the 2PM context. Our proposed fully parametric 2PM (FP2PM) framework comprises very flexible versions of the EM and IM for both continuous and count-valued outcome models and encompasses all implementations of the 2PM found in the literature. Because our modeling approach is potential outcomes (PO) based, it provides a context for clear definition of targeted counterfactual CI parameters of interest. This PO basis also provides a context for identifying the conditions under which such parameters can be consistently estimated using the observable data (via the appropriately specified data generating process). These conditions also ensure that the estimation results are CI. There is substantial literature on statistical testing for model selection in the 2PM context, yet there has been virtually no attention paid to testing the “one-part” null hypothesis. Within our general modeling and estimation framework, we devise a relatively simple test of that null for both continuous and count-valued outcomes. We illustrate our proposed model, method and testing protocol in the context of estimating price effects on the demand for alcohol.

This dissertation proposes the development of a new quantile-based generalized logistic distribution GLDQB, by using the quantile function of the generalized logistic distribution (GLO) as the basic building block. This four-parameter distribution is highly flexible with respect to distributional shape in that it explains extensive levels of skewness and kurtosis through the inclusion of two shape parameters. The parameter space as well as the distributional shape properties are discussed at length. The distribution is characterized through its -moments and an estimation algorithm is presented for estimating the distribution’s parameters with method of -moments estimation. This new distribution is then used to fit and approximate the probability of a data set. / Dissertation (MSc)--University of Pretoria, 2014. / Statistics / MSc / Unrestricted

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Spring hunting season for wild turkey (Meleagris gallopavo) in Mississippi is designed to coincide with peak gobbling activity. The Mississippi Department of Wildlife, Fisheries and Parks (MDWFP) uses brood surveys and hunter observations to forecast gobbling activity. Hunters claimed hunting season does not coincide with regional gobbling peaks. I conducted statewide surveys to assess latitudinal and climatic influences in gobbling activity and used long-term (1996-2008) MDWFP data to evaluate use as a forecasting tool. I observed ≥ 66% of all spring gobbling with an approximate 2-week difference in peak gobbling activity between northern and southern Mississippi. Gobbling in the north was influenced by temperature, wind speed, and cloud cover; in the south, only cloud cover. Long-term data performed poorly predicting gobbling activity (R2 = 0.02 – 0.047, regionally; R2 = 0.06 – 0.09, statewide). Spring hunting season captures most gobbling, including peaks. Data sources should be used cautiously to forecast gobbling activity.

The focus of this work is an industrial refinery model developed by TotalEnergies SE. The model is a sparse, large-scale, nonconvex, mixed-integer nonlinear program (MINLP). The nonconvexity of the problem arises from the many bilinear, trilinear, fractional, logarithmic, exponential, and sigmoidal terms. In order to account for various sources of uncertainty in refinery planning, the industrial refinery model is extended into a two-stage stochastic program, where binary scheduling decisions must be made prior to the realization of the uncertainty, and mixed-integer recourse decisions are made afterwards. Two case studies involving uncertainty are formulated and solved in order to demonstrate the economic and logistical benefits of robust solutions over their deterministic counterparts. A full-space solution strategy is proposed wherein the integrality constraints are relaxed and a multi-step initialization strategy is employed in order to gradually approach the feasible region of the multi-scenario problem. The full-space solution strategy was significantly hampered by difficulties with finding a feasible point and numerical problems. In order to facilitate the identification of a feasible point and to reduce the incidence of numerical difficulties, a hybrid surrogate refinery model was developed using the ALAMO modelling tool. An evaluation procedure was employed to assess the surrogate model, which was shown to be reasonably accurate for most output variables and to be more reliable than the high-fidelity model. Feasible solutions are obtained for the continuous relaxations of both case studies using the full-space solution strategy in conjunction with the surrogate model. In order to solve the original MINLP problems, a decomposition strategy based on the generalized Benders decomposition (GBD) algorithm is proposed. The binary decisions are designated as complicating variables that, when fixed, reduce the full-space problem to a series of independent scenario subproblems. Through the application of the GBD algorithm, feasible mixed-integer solutions are obtained for both case studies, however optimality could not be guaranteed. Solutions obtained via the stochastic programming framework are shown to be more robust than solutions obtained via a deterministic problem formulation. / Thesis / Master of Applied Science (MASc)

A large body of research indicates that worry, anxiety, and depression are present in the modern American psyche at increasingly high levels. Everyday worry can lead to further mental health issues, interpersonal problems, and reduced physical wellbeing and should be reduced when possible. Previous research has examined the benefits of church attendance with varied results; however, understanding the relationship between church attendance and everyday worry could be useful in reducing the effects of worry on this population. The purpose of this quantitative study was to measure self-reported levels and causes of everyday worry among church-goers from three congregations and to examine the relationship among peers when sorted by frequency of church attendance and demographic group. Participants completed demographic questions and the Penn State Worry Questionnaire online. The survey was distributed among 3 congregations in the Raleigh, North Carolina area. The 3 congregations represented a spectrum of churches from the Baptist tradition in an attempt to determine if there were significant differences among conservative, moderate, and liberal churches. Two hundred sixty-six usable surveys were returned, an 84% response rate. Results from the statistical analysis indicated that more frequent church attendance was associated with less worry. Women tended to worry more than men, and younger people tended to worry more than older people. There was no significant relationship between level of worry and church type (conservative, moderate, or liberal).

Automobile accident reconstruction has been facilitated by the development of computer based modules to allow evaluation of evidence gathered at the accident scenes. Although the computer modules are based in fundamental physical laws, an understanding of these laws by the user is required for proper application of the computer model in a given accident scenario. Vehicle collision analysis techniques generally separate the collision into three phases: pre-impact, impact, and post impact. The intent of the research is to provide a generalized model to reconstruct two dimensional impact problems in the area of accident reconstruction. There are currently two modeling techniques used to reconstruct the impact phase: the first technique relying exclusively on impulse-momentum theory coupled with friction and restitution, while the second method combines impulse momentum with a relationship between crush geometry and energy loss. Because each method requires very different inputs, the literature would have us believe that both methods are different. We will show that both methods are derived using the same fundamental physical principles and for any given accident scenario, both methods will provide identical results. Each method will be presented in the form of a MathCAD spread sheet that will allow the user to reconstruct a wide variety of accidents controlling just a few parameters (i.e. mass, rotational inertia, angle of approach, etc...). Both methods will provide step by step graphical representation to assure a solid approach to physical fundamentals. The governing equations to the generalized energy approach will be non-dimensionalized and used to define all of the changes in energy (i.e. also referred to as an impulse in power) as a function of a characteristic velocity. Finally, different methods to consistently determine the direction of the force will be presented when additional information from the accident scene is provided.

A space of pseudoquotients can be described as a space of either single term quotients (the injective case) or the quotient of sequences (the non-injective case) where the parent sets for the numerator and the denominator satisfy particular conditions. The first part of this project is concerned with the minimal of conditions required to have a well-defined set of pseudoquotients. We continue by adding more structure to our sets and discuss the effect on the resultant pseudoquotient. Pseudoquotients can be thought of as extensions of the parent set for the numerator since they include a natural embedding of that set. We answer some questions about the extension properties. One family of these questions involves assuming a structure (algebraic or topological) on a set and asking if the set of pseudoquotients generated has the same structure. A second family of questions looks at maps between two sets and asks if there is an extension of that map between the corresponding pseudoquotients? If so, do the properties of the original map survive the extension? The result of our investigations on the abstract setting will be compared with some well-known spaces of pseudoquotients and Boehmians (a particular case of non-injective pseudoquotients). We will show that the conditions discussed in the first part are satisfied and we will use that to reach conclusions about our extension spaces and the extension maps. The Fourier transform is one of the maps that we will continuously revisit and discuss. Finally many spaces of Boehmians have been introduced where the initial set is a particular class of functions on either locally compact groups R and or a compact group such as a sphere. The natural question is, can we generalize the construction to any locally compact group. In some previous work such construction is discussed, however here we go further; we use characters and define the Fourier transform of integrable and square integrable Boehmians on a locally compact group. Then we discuss the properties of such transform.