7 resultados para Median Voter Hypothesis

em DigitalCommons@The Texas Medical Center


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This research examines the graduation rate experienced by students receiving public education services in the state of Texas. Special attention is paid to that subgroup of Texas students who meet Texas Education Agency criteria for handicapped status. The study is guided by two research questions: What are the high school completion rates experienced by handicapped and nonhandicapped students attending Texas public schools? and What are the predictors of graduation for handicapped and nonhandicapped students?^ In addition, the following hypotheses are explored. Hypothesis 1: Handicapped students attending a Texas public school will experience a lower rate of high school completion than their nonhandicapped counterparts. Hypothesis 2: Handicapped and nonhandicapped students attending school in a Texas public school with a budget above the median budget for Texas public schools will experience a higher rate of high school completion than similar students in Texas public schools with a budget below the median budget. Hypothesis 3: Handicapped and nonhandicapped students attending school in large Texas urban areas will experience a lower rate of high school completion than similar students in Texas public schools in rural areas. Hypothesis 4: Handicapped and nonhandicapped students attending a Texas public school in a county which rates above the state median for food stamps and AFDC recipients will experience a lower rate of high school completion than students living in counties below the median.^ The study will employ extant data from the records of the Texas Education Agency for the 1988-1989 and the 1989-1990 school years, from the Texas Department of Health for the years of 1989 and 1990, and from the 1980 Census.^ The study reveals that nonhandicapped students are graduating with a two year average rate of.906, while handicapped students following an Individualized Educational Program (IEP) achieve a two year average rate of.532, and handicapped students following the regular academic program present a two year average graduation rate of only.371. The presence of other handicapped students, and the school district's average expense per student are found to contribute significantly to the completion rates of handicapped students. Size groupings are used to elucidate the various impacts of these variables on different school districts and different student groups.^ Conclusions and implications are offered regarding the need to reach national consensus on the definition and computation of high school completion for both handicapped and nonhandicapped students, and the need for improved statewide tracking of handicapped completion rates. ^

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The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

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Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

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Mean corpuscular volume, which is an inexpensive and widely available measure to assess, increases in HIV infected individuals receiving zidovudine and stavudine raising the hypothesis that it could be used as a surrogate for adherence.^ The aim of this study was to examine the association between mean corpuscular volume and adherence to antiretroviral therapy among HIV infected children and adolescents aged 0–19 years in Uganda as well as the extent to which changes in mean corpuscular volume predict adherence as determined by virologic suppression.^ The investigator retrospectively reviewed and analyzed secondary data of 158 HIV infected children and adolescents aged 0–19 years who initiated antiretroviral therapy under an observational cohort at the Baylor College of Medicine Children's Foundation - Uganda. Viral suppression was used as the gold standard for monitoring adherence and defined as viral load of < 400 copies/ml at 24 and 48 weeks. ^ Patients were at least 48 weeks on therapy, age 0.2–18.4 years, 54.4% female, 82.3% on zidovudine based regimen, 92% WHO stage III at initiation of therapy, median pre therapy MCV 80.6 fl (70.3–98.3 fl), median CD4% 10.2% (0.3%–28.0%), and mean pre therapy viral load 407,712.9 ± 270,413.9 copies/ml. For both 24 and 48 weeks of antiretroviral therapy, patients with viral suppression had a greater mean percentage change in mean corpuscular volume (15.1% ± 8.4 vs. 11.1% ± 7.8 and 2.3% ± 13.2 vs. -2.7% ± 10.5 respectively). The mean percentage change in mean corpuscular volume was greater in the first 24 weeks of therapy for patients with and without viral suppression (15.1% ± 8.4 vs. 2.3% ± 13.2 and 11.1% ± 7.8 vs. -2.7% ± 10.5 respectively). In the multivariate logistic regression model, percentage change in mean corpuscular volume ≥ 20% was significantly associated with viral suppression (adjusted OR 4.0; CI 1.2–13.3; p value 0.02). The ability of percentage changes in MCV to correctly identify children and adolescents with viral suppression was higher at a cut off of ≥ 20% (90.7%; sensitivity, 31.7%) than at ≥ 9% (82.9%; sensitivity, 78.9%). Negative predictive value was lower at ≥ 20% change (25%; specificity, 84.8%) than at ≥ 9% change (33.3%; specificity, 39.4%).^ Mean corpuscular volume is a useful marker of adherence among children and adolescents with viral suppression. ^

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Background. Polyomavirus reactivation is common in solid-organ transplant recipients who are given immunosuppressive medications as standard treatment of care. Previous studies have shown that polyomavirus infection can lead to allograft failure in as many as 45% of the affected patients. Hypothesis. Ubiquitous polyomaviruses when reactivated by post-transplant immunosuppressive medications may lead to impaired renal function and possibly lower survival prospects. Study Overview. Secondary analysis of data was conducted on a prospective longitudinal study of subjects who were at least 18 years of age and were recipients of liver and/or kidney transplant at Mayo Clinic Scottsdale, Arizona. Methods. DNA extractions of blinded urine and blood specimens of transplant patients collected at Mayo Clinic during routine transplant patient visits were performed at Baylor College of Medicine using Qiagen kits. Virologic assays included testing DNA samples for specific polyomavirus sequences using QPCR technology. De-identified demographic and clinical patient data were merged with laboratory data and statistical analysis was performed using Stata10. Results. 76 patients enrolled in the study were followed for 3.9 years post transplantation. The prevalence of BK virus and JC virus urinary excretion was 30% and 28%. Significant association was observed between JC virus excretion and kidney as the transplanted organ (P = 0.039, Pearson Chi-square test). The median urinary JCV viral loads were two logs higher than those of BKV. Patients that excreted both BKV and JCV appeared to have the worst renal function with a mean creatinine clearance value of 71.6 millimeters per minute. A survival disadvantage was observed for dual shedders of BKV and JCV, log-rank statistics, p = 0.09; 2/5 dual-shedders expired during the study period. Liver transplant and male sex were determined to be potential risk factors for JC virus activation in renal and liver transplant recipients. All patients tested negative for SV40 and no association was observed between polyomavirus excretion and type of immunosuppressive medication (tacrolimus, mycophenolate mofetil, cyclosporine and sirolimus). Conclusions. Polyomavirus reactivation was common after solid-organ transplantation and may be associated with impaired renal function. Male sex and JCV infection may be potential risk factors for viral reactivation; findings should be confirmed in larger studies.^

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The study aim was to determine whether using automated side loader (ASL) trucks in higher proportions compared to other types of trucks for residential waste collection results in lower injury rates (from all causes). The primary hypothesis was that the risk of injury to workers was lower for those who work with ASL trucks than for workers who work with other types of trucks used in residential waste collection. To test this hypothesis, data were collected from one of the nation’s largest companies in the solid waste management industry. Different local operating units (i.e. facilities) in the company used different types of trucks to varying degrees, which created a special opportunity to examine refuse collection injuries and illnesses and the risk reduction potential of ASL trucks.^ The study design was ecological and analyzed end-of-year data provided by the company for calendar year 2007. During 2007, there were a total of 345 facilities which provided residential services. Each facility represented one observation.^ The dependent variable – injury and illness rate, was defined as a facility’s total case incidence rate (TCIR) recorded in accordance with federal OSHA requirements for the year 2007. The TCIR is the rate of total recordable injury and illness cases per 100 full-time workers. The independent variable, percent of ASL trucks, was calculated by dividing the number of ASL trucks by the total number of residential trucks at each facility.^ Multiple linear regression models were estimated for the impact of the percent of ASL trucks on TCIR per facility. Adjusted analyses included three covariates: median number of hours worked per week for residential workers; median number of months of work experience for residential workers; and median age of residential workers. All analyses were performed with the statistical software, Stata IC (version 11.0).^ The analyses included three approaches to classifying exposure, percent of ASL trucks. The first approach included two levels of exposure: (1) 0% and (2) >0 - <100%. The second approach included three levels of exposure: (1) 0%, (2) ≥ 1 - < 100%, and (3) 100%. The third approach included six levels of exposure to improve detection of a dose-response relationship: (1) 0%, (2) 1 to <25%, (3) 25 to <50%, (4) 50 to <75%, (5) 75 to <100%, and (6) 100%. None of the relationships between injury and illness rate and percent ASL trucks exposure levels was statistically significant (i.e., p<0.05), even after adjustment for all three covariates.^ In summary, the present study shows that there is some risk reduction impact of ASL trucks but not statistically significant. The covariates demonstrated a varied yet more modest impact on the injury and illness rate but again, none of the relationships between injury and illness rate and the covariates were statistically significant (i.e., p<0.05). However, as an ecological study, the present study also has the limitations inherent in such designs and warrants replication in an individual level cohort design. Any stronger conclusions are not suggested.^

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BACKGROUND: Mismatch repair deficient (MMRD) colorectal (CRC) or endometrial (EC) cancers in the absence of MLH1 promoter hypermethylation and BRAF mutations are suggestive of Lynch syndrome (LS). Positive germline genetic test results confirm LS. It is unclear if individuals with MMRD tumors but no identified germline mutation or sporadic cause (MMRD+/germline-) have LS. HYPOTHESIS: Since LS is hereditary, individuals with LS should have a stronger family history of LS-related cancers than individuals with sporadic tumors. We hypothesized that MMRD+/germline- CRC and/or EC patients would have less suggestive family histories than LS CRC and/or EC patients. METHODS: 253 individuals with an MMRD CRC or EC who underwent genetic counseling at one institution were included in analysis in 1 of 4 groups: LS, MMRD+/germline-, MMRD+/VUS, sporadic MSI-H (MMRD tumor with MLH1 promoter hypermethylation or BRAF mutation). Family histories were analyzed utilizing MMRpro and PREMM1,2,6. Kruskal-Wallis tests were used to compare family history scores. Logistic regression was used to determine what factors were predictive of LS. RESULTS: MMRD+/germline- individuals had significantly lower median family history scores (PREMM1,2,6=7.3, MMRpro=8.1) than LS individuals (PREMM1,2,6=26.1, MMRpro=89.8, p CONCLUSION: MMRD+/germline- individuals have less suggestive family histories of LS than individuals with LS, but more suggestive family histories than sporadic MSI-H individuals. CRC and/or EC patients with abnormal tumor studies are more likely to have a germline LS mutation if they have a family history suggestive of hereditary cancer. These results imply that the MMRD+/germline- group may not all have LS. This finding highlights the need to determine other somatic, epigenetic or germline causes of MMRD tumors so that these patients and their families can be accurately counseled regarding screening and management.