Gender, minority, and regional-related disparities have been documented in diabetes management. Self-efficacy, the belief in one's ability to carry out the actions mandated by a task, has been identified as a key predictor in glycemic control; however, it has not been investigated in rural, female populations. This cross-sectional, correlation investigation examined the relationships among self-efficacy, depression, and diabetes self-care management in women living in Appalachia with type 2 diabetes. Using Bandura's Social Cognitive Theory, 85 women ages ≥ 21 with type 2 diabetes for a minimum of 6 months who were residents in Appalachia completed the 1) Diabetes Self-Efficacy Scale, 2) Beck Depression Inventory-II, 3)Summary of Diabetes Self-Care Activities, and a 4) Diabetes Health-Related Demographics tool. Descriptive statistics detailed the sample characteristics. ANOVA, chi-square, and independent t-tests were computed for between group differences as they related to depression, various physiologic states, presence of self-efficacy sources, and glycosylated hemoglobin. Pearson correlation coefficients were used to describe the relationships between self-efficacy, depression, and self-care management. Multiple linear regression analyses examined prediction models for glucose control while controlling for potential confounders. Eighty-four Caucasian and one African-American enrolled in the study with a mean age of 61. The mean time since diabetes diagnosis was 7 years with a mean glycosylated hemoglobin value of 6.9% (SD=1.3). Higher self-efficacy scores were associated with a lower glycosylated hemoglobin (r-.30, p=.005) and ability to choose foods best to maintain a healthy eating plan(r-.415, p=.001). The sources of self-efficacy associated with enhanced self-care management were mastery experience and vicarious experience. There were no significant relationships between self-efficacy and depression or depression and glycosylated hemoglobin. The diabetes self-care management regression model resulted in self-efficacy and education accounting for 7.5% of the variance in glycosylated hemoglobin. Study findings support the social cognitive theory and the utility of self-efficacy as a predictor of glycemic control. Depression was not found to be a significant obstacle in this Appalachian population. Comprehending the significant relationship between self-efficacy and diabetes self-care management allows providers to modify their interventions when caring for women type 2 diabetes in the region.

Lung cancer remains the leading cause of cancer deaths in the United States despite public health campaigns aimed at reducing its rate of mortality. Kentucky is the state with the highest lung cancer incidence and mortality. This study aims to assess the impact of misclassification of cause of death from Lung Cancer in Kentucky for the period 1979 to 2002. We will examine the potential competing classification of death for two other smoking-related diseases, Chronic Obstructive Pulmonary Disease (COPD) and Emphysema. Age-adjusted mortality rates for these diseases for white males were obtained from the National Center for Health Statistics. There was little evidence that any misclassification between COPD or Emphysema mortality rates was in agreement with the rising lung cancer rates in Kentucky. The long-term increase in lung cancer mortality in Kentucky is likely because of a combination of risk effects between smoking and other risk-factors for this disease.

Testing the homogeneity of variances is an important problem in many applications since statistical methods of frequent use, such as ANOVA, assume equal variances for two or more groups of data. However, testing the equality of variances is a difficult problem due to the fact that many of the tests are not robust against non-normality. It is known that the kurtosis of the distribution of the source data can affect the performance of the tests for variance. We review the classical tests and their latest, more robust modifications, some other tests that have recently appeared in the literature, and use bootstrap and permutation techniques to test for equal variances. We compare the performance of these tests under different types of distributions, sample sizes and true ratios of variances of the populations. Monte-Carlo methods are used in this study to calculate empirical powers and type I errors under different settings.

This thesis looks at the corequisite developmental math program at East Tennessee State University (ETSU) and compares the effectiveness to the previous developmental math program by comparing the student outcomes in MATH 1530. MATH 1530 is a non-calculus based statistic and probability course that satisfies most majors’ general education math requirements. ETSU sees approximately 1,000 students a year pass through MATH 1530 which is around 6.7% of the total enrollment at ETSU[9]. We are interested in the last five years of the developmental math program before it was changed to corequisite developmental math and the first five years of corequisite developmental math program. Our research compares the grades of the students in these courses to evaluate if one program is more successful in students’ grade outcomes. Our findings show no change in class medians but a change in the class means in favor of the corequisite developmental math program.

Coalescent theory is a method often used by population geneticists in order to make inferences about evolutionary parameters. The coalescent is a stochastic model that approximates ancestral relationships among genes. An understanding of the coalescent pattern of a sample of sequences, along with some knowledge of the mutations that have occurred, provides information about the evolutionary forces that have acted on the population. Processes such as migration, recombination, variable population size, or natural selection are the forces that affect the genealogies and lead to genetic variability in a sample. Coalescent theory provides a statistical description of the variability in the sample, which in turn leads to inference about evolutionary parameters such as population size, population growth rates, and migration rates. Several methods have been developed that model the coalescent under different sets of evolutionary assumptions. We have examined and compared three computer packages that estimate parameters under the coalescent model: LAMARC, Genetree, and UPBLUE. These are not commercial computer programs, but have been developed by researchers for their own use and made available to others. Their performance in various areas has not been previously well established. We compared the programs in the general areas of model assumptions, availability, usability, and results. No single program is superior to the others in all areas, but each have strengths and weakness. Program selection must be based on the researcher's data, goals and preferences. This comparison should help population geneticists determine which program would be most applicable for their data and research.

Linear mixed models are frequently used to analyze data with random effects and/or repeated measures. A common approach to such analyses requires choosing a covariance structure. Information criteria, such as AIC and BIC, are often used by statisticians to help with this task. However, these criteria do not always point to the true covariance structure and therefore the wrong covariance structure is sometimes chosen. Once this step is complete, Wald statistics are used to test fixed effects. Degrees of freedom for these statistics are not known. However, there are approximation methods, such as Kenward and Roger (KR) and Satterthwaite (SW) that have been shown to work well in some situations. Schaalje et al. (2002) concluded that the KR method would perform at least as well as or better than the SW method in many cases assuming that the covariance structure was known. On the other hand, Keselman et al. (1999) concluded that the performance of the SW method when the covariance structure was selected using AIC was poor for negative pairings of treatment sizes and covariance matrices and small sample sizes. Our study used simulations to investigate Type I error rates in test of fixed effects using Wald statistics with the KR adjustment method, incorporating the selection of the covariance structure using AIC and BIC. Performance of the AIC and BIC criteria in selecting the true covariance structure was also studied. The MIXED procedure (SAS v. 9) was used to analyze each simulated data set. Type I error rates from the best AIC and BIC models were always higher than target values. However, Type I error rates obtained by using the BIC criterion were better than those obtained by using the AIC criterion. Type I error rates for the correct models were often adequate depending on the sample size and complexity of covariance structure. Performance of AIC and BIC was poor. This could be a consequence of small sample sizes and the high number of covariance structures these criteria had to choose from.

People at risk for blood clots are often treated with anticoagulants, warfarin is such an anticoagulant. The dose's effect is measured by comparing the time for blood to clot to a control time called an INR value. Previous anticoagulant studies have addressed agreement between fingerstick (POC) devices and the standard laboratory, however these studies rely on mathematical formulas as criteria for clinical evaluations, i.e. clinical evaluation vs. precision and bias. Fourteen such criteria were found in the literature. There exists little consistency among these criteria for assessing clinical agreement, furthermore whether these methods of assessing agreement are reasonable estimates of clinical decision-making is unknown and has yet to be validated. One previous study compared actual clinical agreement by having two physicians indicate a dosing decision based on patient history and INR values. This analysis attempts to justify previously used mathematical criteria for clinical agreement. Generalized additive models with smoothing spline estimates were calculated for each of the 14 criteria and compared to the smoothing spline estimate for the method using actual physician decisions (considered the "gold standard"). The area between the criteria method spline and the gold standard method spline served as the comparison, using bootstrapping for statistical inference. Although some of the criteria methods performed better than others, none of them matched the gold standard. This stresses the need for clinical assessment of devices.

In this study a service-learning project was conducted with secondary students in a construction technology based course. Three research questions were considered; (1) does service learning projects help to engage student participation, (2) can students learn the course curriculum while participating in a service learning project, and (3) is there a correlation between student participation and student learning as it pertains to service learning projects? The data was collected through surveys, observations, interviews, and evaluations. The researcher concluded the following from the study; 92% of the students were actively participating in the two week service project, 76% of the students learned the curriculum for the unit in a satisfactory manner, and it was determined that there is a significant correlation between students participation or commitment to the service learning project with how well the students learned the curriculum for that unit.

This thesis investigates the suitability of thermo-kinetically recycled plastics for use in commercial product applications using finite element analysis and statistics. Different recycled material blends were tested and evaluated for their use in commercial product applications. There are six different blends of thermo-kinetically recycled plastics used for testing and CATIA is used for finite element analysis. The different types of thermo-kinetically recycled plastics blends are: pop bottles made of PolyethyleneTeraphthalate (PET), milk jugs made of High-Density Polyethylene (HDPE), Vinyl seats made of Poly Vinyl Chloride (PVC) and small amount of Polypropylene (PP) and Urethane, electronic scrap made of engineering resins like Acrylo-Nitrile-Butadiene Styrene (ABS), Polystyrene (PS) and Polycarbonate (PC), agriculture waste consisting of Low Density Polyethylene (LDPE), industrial waste consisting of Nylon (PA66) and PolyethyleneTeraphthalate (PET), household waste consisting of Polystyrene (PS). The methods employed during the study include three phases for each of six blends available: 1.Density, tensile and impact testing of each blend 2.Correlation of mechanical properties to blend 3.Finite element analysis of the service performance of a product made from each thermo-kinetically recycled plastic blend This thesis shows that some of the recycled plastics materials that were tested are qualified to be used in the pallet. Those materials that qualified were Industrial waste consisting of Nylon and PolyethyleneTeraphthalate, household waste consisting of Polystyrene.

The class of generalized feedback shift register (GFSR) random number generators was a promising method for random number generation in the 1980's, but was abandoned because of some flaws such as poor performance on certain tests for randomness. The poor performance may be due to the choice of primitive polynomials used in the generators, rather than inherent flaws in the method. The original GFSR generators were all based on primitive trinomials. This project examines several alternative choices of primitive polynomials with more than one "interior" term to address this problem and hopefully provide access to good random number generators.