8 resultados para TURF analysis, Binary programming, product design
em DigitalCommons@The Texas Medical Center
Resumo:
Electronic waste is a fairly new and largely unknown phenomenon. Accordingly, governments have only recently acknowledged electronic waste as a threat to the environment and public health. In attempting to mitigate the hazards associated with this rapidly growing toxic waste stream, governments at all levels have started to implement e-waste management programs. The legislation enacted to create these programs is based on extended producer responsibility or EPR policy. ^ EPR shifts the burden of final disposal of e-waste from the consumer or municipal solid waste system to the manufacturer of electronic equipment. Applying an EPR policy is intended to send signals up the production chain to the manufacturer. The desired outcome is to change the methods of production in order to reduce production outputs/inputs with the ultimate goal of changing product design. This thesis performs a policy analysis of the current e-waste policies at the federal and state level of government, focusing specifically on Texas e-waste policies. ^ The Texas e-waste law known, as HB 2714 or the Texas Computer TakeBack Law, requires manufacturers to provide individual consumers with a free and convenient method for returning their used computers to manufacturers. The law is based on individual producer responsibility and shared responsibility among consumer, retailers, recyclers, and the TCEQ. ^ Using a set of evaluation criteria created by the Organization for Economic Co-operation and Development, the Texas e-waste law was examined to determine its effectiveness at reducing the threat of e-waste in Texas. Based on the outcomes of the analysis certain recommendations were made for the legislature to incorporate into HB 2714. ^ The results of the policy analysis show that HB 2714 is a poorly constructed law and does not provide the desired results seen in other states with EPR policies. The TakeBack Law does little to change the collection methods of manufacturers and even less to change their production habits. If the e-waste problem is to be taken seriously, HB 2714 must be amended to reflect the proposed changes in this thesis.^
Resumo:
The purpose of this research was development of a method of estimating nutrient availability in populations as approximated by supermarket purchase records. Demographic information describing 12,516 panel households was obtained from a marketing and advertising program operated by H. E. Butt Grocery Company of San Antonio, Texas. A non-probability sample of 2,161 households meeting expenditure criteria was selected and all purchases of dairy products for this sample of households were organized into a database constructed to facilitate the retrieval, aggregation, and analysis of dairy product purchases and their nutrient contents. Two hypotheses were tested: (1) no difference would be found between Hispanic and non-Hispanic purchases of dairy product categories during the study period and (2) no difference would be found between Hispanic and non-Hispanic purchases of nutrients contained in those dairy products during the thirteen-week study period.^ Food purchase records were used to estimate nutrient exposure on a weekly, per capita basis for Hispanic and non-Hispanic households by linking some 40,000 dairy purchase Universal Product code (UPC) numbers with food composition values contained in USDA Handbook 8-1. Results of this study suggest Hispanic sample households consistently purchased fewer dairy products than did non-Hispanic sample households and consequently had fewer nutrients available from dairy purchases. While weekly expenditures for dairy products among the sample households remained relatively constant during the study period, shifts in the types of dairy products purchased were observed. The effect of ethnicity on dairy product and nutrient purchases was significant over the thirteen-week period. A database consisting of customer, household, and purchase information can be developed to successfully associate food item UPC numbers with a standard reference of food composition to estimate nutrient availability in a population over extended periods of time. ^
Resumo:
Objectives. Triple Negative Breast Cancer (TNBC) lack expression of estrogen receptors (ER), progesterone receptors (PR), and absence of Her2 gene amplification. Current literature has identified TNBC and over-expression of cyclo-oxygenase-2 (COX-2) protein in primary breast cancer to be independent markers of poor prognosis in terms of overall and distant disease free survival. The purpose of this study was to compare COX-2 over-expression in TNBC patients to those patients who expressed one or more of the three tumor markers (i.e. ER, and/or PR, and/or Her2).^ Methods. Using a secondary data analysis, a cross-sectional design was implemented to examine the association of interest. Data collected from two ongoing protocols titled "LAB04-0657: a model for COX-2 mediated bone metastasis (Specific aim 3)" and "LAB04-0698: correlation of circulating tumor cells and COX-2 expression in primary breast cancer metastasis" was used for analysis. A sample of 125 female patients was analyzed using Chi-square tests and logistic regression models. ^ Results. COX-2 over-expression was present in 33% (41/125) and 28% (35/124) patients were identified as having TNBC. TNBC status was associated with elevated COX-2 expression (OR= 3.34; 95% CI= 1.40–8.22) and high tumor grade (OR= 4.09; 95% CI= 1.58–10.82). In a multivariable analysis, TNBC status was an important predictor of COX-2 expression after adjusting for age, menopausal status, BMI, and lymph node status (OR= 3.31; 95% CI: 1.26–8.67; p=0.01).^ Conclusion. TNBC is associated with COX-2 expression—a known marker of poor prognosis in patients with operable breast cancer. Replication of these results in a study with a larger sample size, or a future randomized clinical trial demonstrating an improved prognosis with COX-2 suppression in these patients would support this hypothesis.^
Resumo:
Background. Research into methods for recovery from fatigue due to exercise is a popular topic among sport medicine, kinesiology and physical therapy. However, both the quantity and quality of studies and a clear solution of recovery are lacking. An analysis of the statistical methods in the existing literature of performance recovery can enhance the quality of research and provide some guidance for future studies. Methods: A literature review was performed using SCOPUS, SPORTDiscus, MEDLINE, CINAHL, Cochrane Library and Science Citation Index Expanded databases to extract the studies related to performance recovery from exercise of human beings. Original studies and their statistical analysis for recovery methods including Active Recovery, Cryotherapy/Contrast Therapy, Massage Therapy, Diet/Ergogenics, and Rehydration were examined. Results: The review produces a Research Design and Statistical Method Analysis Summary. Conclusion: Research design and statistical methods can be improved by using the guideline from the Research Design and Statistical Method Analysis Summary. This summary table lists the potential issues and suggested solutions, such as, sample size calculation, sports specific and research design issues consideration, population and measure markers selection, statistical methods for different analytical requirements, equality of variance and normality of data, post hoc analyses and effect size calculation.^
Resumo:
In numerous intervention studies and education field trials, random assignment to treatment occurs in clusters rather than at the level of observation. This departure of random assignment of units may be due to logistics, political feasibility, or ecological validity. Data within the same cluster or grouping are often correlated. Application of traditional regression techniques, which assume independence between observations, to clustered data produce consistent parameter estimates. However such estimators are often inefficient as compared to methods which incorporate the clustered nature of the data into the estimation procedure (Neuhaus 1993).1 Multilevel models, also known as random effects or random components models, can be used to account for the clustering of data by estimating higher level, or group, as well as lower level, or individual variation. Designing a study, in which the unit of observation is nested within higher level groupings, requires the determination of sample sizes at each level. This study investigates the design and analysis of various sampling strategies for a 3-level repeated measures design on the parameter estimates when the outcome variable of interest follows a Poisson distribution. ^ Results study suggest that second order PQL estimation produces the least biased estimates in the 3-level multilevel Poisson model followed by first order PQL and then second and first order MQL. The MQL estimates of both fixed and random parameters are generally satisfactory when the level 2 and level 3 variation is less than 0.10. However, as the higher level error variance increases, the MQL estimates become increasingly biased. If convergence of the estimation algorithm is not obtained by PQL procedure and higher level error variance is large, the estimates may be significantly biased. In this case bias correction techniques such as bootstrapping should be considered as an alternative procedure. For larger sample sizes, those structures with 20 or more units sampled at levels with normally distributed random errors produced more stable estimates with less sampling variance than structures with an increased number of level 1 units. For small sample sizes, sampling fewer units at the level with Poisson variation produces less sampling variation, however this criterion is no longer important when sample sizes are large. ^ 1Neuhaus J (1993). “Estimation efficiency and Tests of Covariate Effects with Clustered Binary Data”. Biometrics , 49, 989–996^
Resumo:
Many studies in biostatistics deal with binary data. Some of these studies involve correlated observations, which can complicate the analysis of the resulting data. Studies of this kind typically arise when a high degree of commonality exists between test subjects. If there exists a natural hierarchy in the data, multilevel analysis is an appropriate tool for the analysis. Two examples are the measurements on identical twins, or the study of symmetrical organs or appendages such as in the case of ophthalmic studies. Although this type of matching appears ideal for the purposes of comparison, analysis of the resulting data while ignoring the effect of intra-cluster correlation has been shown to produce biased results.^ This paper will explore the use of multilevel modeling of simulated binary data with predetermined levels of correlation. Data will be generated using the Beta-Binomial method with varying degrees of correlation between the lower level observations. The data will be analyzed using the multilevel software package MlwiN (Woodhouse, et al, 1995). Comparisons between the specified intra-cluster correlation of these data and the estimated correlations, using multilevel analysis, will be used to examine the accuracy of this technique in analyzing this type of data. ^
Resumo:
Do siblings of centenarians tend to have longer life spans? To answer this question, life spans of 184 siblings for 42 centenarians have been evaluated. Two important questions have been addressed in analyzing the sibling data. First, a standard needs to be established, to which the life spans of 184 siblings are compared. In this report, an external reference population is constructed from the U.S. life tables. Its estimated mortality rates are treated as baseline hazards from which the relative mortality of the siblings are estimated. Second, the standard survival models which assume independent observations are invalid when correlation within family exists, underestimating the true variance. Methods that allow correlations are illustrated by three different methods. First, the cumulative relative excess mortality between siblings and their comparison group is calculated and used as an effective graphic tool, along with the Product Limit estimator of the survival function. The variance estimator of the cumulative relative excess mortality is adjusted for the potential within family correlation using Taylor linearization approach. Second, approaches that adjust for the inflated variance are examined. They are adjusted one-sample log-rank test using design effect originally proposed by Rao and Scott in the correlated binomial or Poisson distribution setting and the robust variance estimator derived from the log-likelihood function of a multiplicative model. Nether of these two approaches provide correlation estimate within families, but the comparison with the comparison with the standard remains valid under dependence. Last, using the frailty model concept, the multiplicative model, where the baseline hazards are known, is extended by adding a random frailty term that is based on the positive stable or the gamma distribution. Comparisons between the two frailty distributions are performed by simulation. Based on the results from various approaches, it is concluded that the siblings of centenarians had significant lower mortality rates as compared to their cohorts. The frailty models also indicate significant correlations between the life spans of the siblings. ^
Resumo:
Childhood overweight and obesity are two major public health problems that are of economic and medical concern in the world today (Lobstein, Baur, & Uauy, 2004). Overweight conditions in childhood are important because they are widely prevalent, serious, and carry lifetime consequences for health and well being (Lobstein et al., 2004). Several studies have shown an association between television viewing and obesity in all age groups (Caroli, Argentieri, Cardone, & Masi, 2004; Harper, 2006; Vandewater & Huang, 2006; Wiecha et al., 2006). One mechanism that potentially links television viewing to childhood obesity is food advertising (Story, 2003). ^ The purpose of this study was to examine the types of foods advertised on children's television programming and to determine if there have been any changes in the number and types of commercials over the last 13 years. In addition, the food content of the advertisements was compared to the 2005 Dietary Guidelines to determine if the foods targeted were consistent with the current recommendations. Finally, each television network was analyzed individually to determine any differences between advertising on cable and regular programming. ^ A descriptive analysis was conducted on the most commonly advertised commercials during children's television programming on Saturday morning from 7 a.m. to 10:30 a.m. A total of 10 major television networks were viewed on three different Saturday mornings during June and July 2007. Commercial advertising accounted for approximately 19% of children's total viewing time. Of the 3,185 commercials, 28.5% were for foods, 67.7% were for non-food items, and 3.8% were PSAs. On average, there were 30 commercial advertisements and PSAs per hour, of which approximately nine were for food. ^ Of the 907 food advertisements, 72.0% were for foods classified in the fats, oils, and sugar group. The next largest group (17.3%) was for restaurant food of which 15.3% were for unhealthy/fast food restaurant fare. The most frequently advertised food product on Saturday morning television was regular cereal, accounting for 43.9% of all food advertisements. ^ Cable and regular programming stations varied slightly in the amount, length, and category of commercials. Cable television had about 50% less commercials and PSAs (1098) than regular programming (2087), but only had approximately 150 minutes less total commercial and PSA time; therefore, cable, in general, had longer commercials than regular programming. Overall, cable programming had more advertisements encouraging increased physical activity and positive nutrition behavior with less commercials focusing on the fats, oils, and sugar groups, compared to regular programming. ^ During the last 13 years, food advertisements have not improved, despite the recent IOM report on marketing foods to children (Institute of Medicine-Committee on Food Marketing and the Diets of Children and Youth, 2005), although the frequency of food advertisements has improved slightly. Children are now viewing an average of one food advertisement every 7 minutes, compared to one food advertisement every 5 minutes in 1994 (Kotz & Story, 1994). Therefore, manufacturers are putting a greater emphasis on advertising other products to children. Despite the recent attention to the issue of marketing unhealthy foods to children through television advertisements, not much progress has been noted since 1994. Further advocacy and regulatory issues concerning the content of advertisements during Saturday morning TV need to be explored. ^