437 resultados para Statistical hypothesis testing.


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Operational modal analysis (OMA) is prevalent in modal identifi cation of civil structures. It asks for response measurements of the underlying structure under ambient loads. A valid OMA method requires the excitation be white noise in time and space. Although there are numerous applications of OMA in the literature, few have investigated the statistical distribution of a measurement and the infl uence of such randomness to modal identifi cation. This research has attempted modifi ed kurtosis to evaluate the statistical distribution of raw measurement data. In addition, a windowing strategy employing this index has been proposed to select quality datasets. In order to demonstrate how the data selection strategy works, the ambient vibration measurements of a laboratory bridge model and a real cable-stayed bridge have been respectively considered. The analysis incorporated with frequency domain decomposition (FDD) as the target OMA approach for modal identifi cation. The modal identifi cation results using the data segments with different randomness have been compared. The discrepancy in FDD spectra of the results indicates that, in order to fulfi l the assumption of an OMA method, special care shall be taken in processing a long vibration measurement data. The proposed data selection strategy is easy-to-apply and verifi ed effective in modal analysis.

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This thesis explored the development of statistical methods to support the monitoring and improvement in quality of treatment delivered to patients undergoing coronary angioplasty procedures. To achieve this goal, a suite of outcome measures was identified to characterise performance of the service, statistical tools were developed to monitor the various indicators and measures to strengthen governance processes were implemented and validated. Although this work focused on pursuit of these aims in the context of a an angioplasty service located at a single clinical site, development of the tools and techniques was undertaken mindful of the potential application to other clinical specialties and a wider, potentially national, scope.

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Background: Random Breath Testing (RBT) is the main drink driving law enforcement tool used throughout Australia. International comparative research considers Australia to have the most successful RBT program compared to other countries in terms of crash reductions (Erke, Goldenbeld, & Vaa, 2009). This success is attributed to the programs high intensity (Erke et al., 2009). Our review of the extant literature suggests that there is no research evidence that indicates an optimal level of alcohol breath testing. That is, we suggest that no research exists to guide policy regarding whether or not there is a point at which alcohol related crashes reach a point of diminishing returns as a result of either saturated or targeted RBT testing. Aims: In this paper we first provide an examination of RBTs and alcohol related crashes across Australian jurisdictions. We then address the question of whether or not an optimal level of random breath testing exists by examining the relationship between the number of RBTs conducted and the occurrence of alcohol-related crashes over time, across all Australian states. Method: To examine the association between RBT rates and alcohol related crashes and to assess whether an optimal ratio of RBT tests per licenced drivers can be determined we draw on three administrative data sources form each jurisdiction. Where possible data collected spans January 1st 2000 to September 30th 2012. The RBT administrative dataset includes the number of Random Breath Tests (RBTs) conducted per month. The traffic crash administrative dataset contains aggregated monthly count of the number of traffic crashes where an individual’s recorded BAC reaches or exceeds 0.05g/ml of alcohol in blood. The licenced driver data were the monthly number of registered licenced drivers spanning January 2000 to December 2011. Results: The data highlights that the Australian story does not reflective of all States and territories. The stable RBT to licenced driver ratio in Queensland (of 1:1) suggests a stable rate of alcohol related crash data of 5.5 per 100,000 licenced drivers. Yet, in South Australia were a relative stable rate of RBT to licenced driver ratio of 1:2 is maintained the rate of alcohol related traffic crashes is substantially less at 3.7 per 100,000. We use joinpoint regression techniques and varying regression models to fit the data and compare the different patterns between jurisdictions. Discussion: The results of this study provide an updated review and evaluation of RBTs conducted in Australia and examines the association between RBTs and alcohol related traffic crashes. We also present an evidence base to guide policy decisions for RBT operations.

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Background Random Breath Testing (RBT) remains a central enforcement strategy to deter and apprehend drink drivers in Queensland (Australia). Despite this, there is little published research regarding the exact drink driving apprehension rates across the state as measured through RBT activities. Aims The aim of the current study was to examine the prevalence of apprehending drink drivers in urban versus rural areas. Methods The Queensland Police Service provided data relating to the number of RBT conducted and apprehensions for the period 1 January 2000 to 31 December 2011. Results In the period, 35,082,386 random breath tests (both mobile and stationary) were conducted in Queensland which resulted in 248,173 individuals being apprehended for drink driving offences. Overall drink driving apprehension rates appear to have decreased across time. Close examination of the data revealed that the highest proportion of drink driving apprehensions (when compared with RBT testing rates) was in the Northern and Far Northern regions of Queensland (e.g., rural areas). In contrast, the lowest proportions were observed within the two Brisbane metropolitan regions (e.g., urban areas). However, differences in enforcement styles across the urban and rural regions need to be considered. Discussion and conclusions The research presentation will further outline the major findings of the study in regards to maximising the efficiency of RBT operations both within urban and rural areas of Queensland, Australia.

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Recent association studies in multiple sclerosis (MS) have identified and replicated several single nucleotide polymorphism (SNP) susceptibility loci including CLEC16A, IL2RA, IL7R, RPL5, CD58, CD40 and chromosome 12q13–14 in addition to the well established allele HLA-DR15. There is potential that these genetic susceptibility factors could also modulate MS disease severity, as demonstrated previously for the MS risk allele HLA-DR15. We investigated this hypothesis in a cohort of 1006 well characterised MS patients from South-Eastern Australia. We tested the MS-associated SNPs for association with five measures of disease severity incorporating disability, age of onset, cognition and brain atrophy. We observed trends towards association between the RPL5 risk SNP and time between first demyelinating event and relapse, and between the CD40 risk SNP and symbol digit test score. No associations were significant after correction for multiple testing. We found no evidence for the hypothesis that these new MS disease risk-associated SNPs influence disease severity.

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OBJECTIVE: To examine a polymorphism within the 3' untranslated region of the leukemia inhibitory factor gene for an association with multiple sclerosis within an Australian case-control population. METHODS: A test group of 121 unrelated multiple sclerosis patients, of Caucasian origin, and 121 controls, matched for ethnicity, sex and age (+/-5 years) were included in the study. The LIF 3' UTR StuI polymorphism was genotyped by restriction fragment length polymorphism analysis. Statistical analysis of genotype and allele frequencies included Hardy-Weinberg law and conventional contingency table analysis incorporating the standard chi-squared test for independence. RESULTS: Allelic and genotype frequencies did not demonstrate a significant association between the case and control groups for the tested LIF 3' UTR StuI polymorphism. CONCLUSION: The results indicate that the LIF 3' UTR StuI polymorphism is not associated with multiple sclerosis, however we cannot exclude the hypothesis that other polymorphic alleles of LIF could be implicated in MS susceptibility.

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Migraine with aura (MA) is a subtype of typical migraine. Migraine with aura (MA) also encompasses a rare severe subtype Familial Hemiplegic Migraine (FHM) with several known genetic loci. The type 2 FHM (FHM-2) susceptibility locus maps to chromosome 1q23 and mutations in the ATP1A2 gene at this site have recently been implicated. We have previously provided evidence of linkage of typical migraine (predominantly MA) to microsatellite markers on chromosome 1, in the 1q31 and 1q23 regions. In this study, we have undertaken a large genomic investigation involving candidate genes that lie within the chromosome 1q23 and 1q31 regions using an association analysis approach. Methods We have genotyped a large population of case-controls (243 unrelated Caucasian migraineurs versus 243 controls) examining a set of 5 single nucleotide polymorphisms (SNPs) and the Fas Ligand dinucleotide repeat marker, located within the chromosome 1q23 and 1q31 regions. Results Several genes have been studied including membrane protein (ATP 1 subtype A4 and FasL), cytoplasmic glycoprotein (CASQ 1) genes and potassium (KCN J9 and KCN J10) and calcium (CACNA1E) channel genes in 243 migraineurs (including 85% MA and 15% of migraine without aura (MO)) and 243 matched controls. After correction for multiple testing, chi-square results showed non-significant P values (P > 0.008) across all SNPs (and a CA repeat) tested in these different genes, however results with the KCN J10 marker gave interesting results (P = 0.02) that may be worth exploring further in other populations. Conclusion These results do not show a significant role for the tested candidate gene variants and also do not support the hypothesis that a common chromosome 1 defective gene influences both FHM and the more common forms of migraine.

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Nitrous oxide emissions from soil are known to be spatially and temporally volatile. Reliable estimation of emissions over a given time and space depends on measuring with sufficient intensity but deciding on the number of measuring stations and the frequency of observation can be vexing. The question of low frequency manual observations providing comparable results to high frequency automated sampling also arises. Data collected from a replicated field experiment was intensively studied with the intention to give some statistically robust guidance on these issues. The experiment had nitrous oxide soil to air flux monitored within 10 m by 2.5 m plots by automated closed chambers under a 3 h average sampling interval and by manual static chambers under a three day average sampling interval over sixty days. Observed trends in flux over time by the static chambers were mostly within the auto chamber bounds of experimental error. Cumulated nitrous oxide emissions as measured by each system were also within error bounds. Under the temporal response pattern in this experiment, no significant loss of information was observed after culling the data to simulate results under various low frequency scenarios. Within the confines of this experiment observations from the manual chambers were not spatially correlated above distances of 1 m. Statistical power was therefore found to improve due to increased replicates per treatment or chambers per replicate. Careful after action review of experimental data can deliver savings for future work.

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In South and Southeast Asia, postharvest loss causes material waste of up to 66% in fruits and vegetables, 30% in oilseeds and pulses, and 49% in roots and tubers. The efficiency of postharvest equipment directly affects industrial-scale food production. To enhance current processing methods and devices, it is essential to analyze the responses of food materials under loading operations. Food materials undergo different types of mechanical loading during postharvest and processing stages. Therefore, it is important to determine the properties of these materials under different types of loads, such as tensile, compression, and indentation. This study presents a comprehensive analysis of the available literature on the tensile properties of different food samples. The aim of this review was to categorize the available methods of tensile testing for agricultural crops and food materials to investigate an appropriate sample size and tensile test method. The results were then applied to perform tensile tests on pumpkin flesh and peel samples, in particular on arc-sided samples at a constant loading rate of 20 mm min-1. The results showed the maximum tensile stress of pumpkin flesh and peel samples to be 0.535 and 1.45 MPa, respectively. The elastic modulus of the flesh and peel samples was 6.82 and 25.2 MPa, respectively, while the failure modulus values were 14.51 and 30.88 MPa, respectively. The results of the tensile tests were also used to develop a finite element model of mechanical peeling of tough-skinned vegetables. However, to study the effects of deformation rate, moisture content, and texture of the tissue on the tensile responses of food materials, more investigation needs to be done in the future.

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Migraine is a painful and debilitating disorder with a significant genetic component. Steroid hormones, in particular estrogen, have long been considered to play a role in migraine, as variations in hormone levels are associated with migraine onset in many sufferers of the disorder. Steroid hormones mediate their activity via hormone receptors, which have a wide tissue distribution. Estrogen receptors have been localized to the brain in regions considered to be involved in migraine pathogenesis. Hence it is possible that genetic variation in the estrogen receptor gene may play a role in migraine susceptibility. This study thus examined the estrogen receptor 1 (ESRα) gene for a potential role in migraine pathogenesis and susceptibility. A population-based cohort of 224 migraine sufferers and 224 matched controls were genotyped for the G594A polymorphism located in exon 8 of the ESR1 gene. Statistical analysis indicated a significant difference between migraineurs and non-migraineurs in both the allele frequencies (P=0.003) and genotype distributions (P=0.008) in this sample. An independent follow-up study was then undertaken using this marker in an additional population-based cohort of 260 migraine sufferers and 260 matched controls. This resulted in a significant association between the two groups with regard to allele frequencies (P=8×10−6) and genotype distributions (P=4×10−5). Our findings support the hypothesis that genetic variation in hormone receptors, in particular the ESR1 gene, may play a role in migraine.

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This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

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Skin cancer is one of the most commonly occurring cancer types, with substantial social, physical, and financial burdens on both individuals and societies. Although the role of UV light in initiating skin cancer development has been well characterized, genetic studies continue to show that predisposing factors can influence an individual's susceptibility to skin cancer and response to treatment. In the future, it is hoped that genetic profiles, comprising a number of genetic markers collectively involved in skin cancer susceptibility and response to treatment or prognosis, will aid in more accurately informing practitioners' choices of treatment. Individualized treatment based on these profiles has the potential to increase the efficacy of treatments, saving both time and money for the patient by avoiding the need for extensive or repeated treatment. Increased treatment responses may in turn prevent recurrence of skin cancers, reducing the burden of this disease on society. Currently existing pharmacogenomic tests, such as those that assess variation in the metabolism of the anticancer drug fluorouracil, have the potential to reduce the toxic effects of anti-tumor drugs used in the treatment of non-melanoma skin cancer (NMSC) by determining individualized appropriate dosage. If the savings generated by reducing adverse events negate the costs of developing these tests, pharmacogenomic testing may increasingly inform personalized NMSC treatment.

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Migraine is classified by the World Health Organization (WHO) as being one of the top 20 most debilitating diseases. According to the neurovascular hypothesis, neuroinflammation may promote the activation and sensitisation of meningeal nociceptors, inducing the persistent throbbing headache characterized in migraine. The tumor necrosis factor (TNF) gene cluster, made up of TNFα, lymphotoxin α (LTA), and lymphotoxin β (LTB), has been implicated to influence the intensity and duration of local inflammation. It is thought that sterile inflammation mediated by LTA, LTB, and TNFα contributes to threshold brain excitability, propagation of neuronal hyperexcitability and thus initiation and maintenance of a migraine attack. Previous studies have investigated variants within the TNF gene cluster region in relation to migraine susceptibility, with largely conflicting results. The aim of this study was to expand on previous research and utilize a large case-control cohort and range of variants within the TNF gene cluster to investigate the role of the TNF gene cluster in migraine. Nine single nucleotide polymorphisms (SNPs) were selected for investigation as follows: rs1800683, rs2229094, rs2009658, rs2071590, rs2239704, rs909253, rs1800630, rs1800629, and rs3093664. No significant association with migraine susceptibility was found for any of the SNPs tested, with further testing according to migraine subtype and gender also showing no association for disease risk. Haplotype analysis showed that none of the tested haplotypes were significantly associated with migraine.

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This thesis explored the knowledge and reasoning of young children in solving novel statistical problems, and the influence of problem context and design on their solutions. It found that young children's statistical competencies are underestimated, and that problem design and context facilitated children's application of a wide range of knowledge and reasoning skills, none of which had been taught. A qualitative design-based research method, informed by the Models and Modeling perspective (Lesh & Doerr, 2003) underpinned the study. Data modelling activities incorporating picture story books were used to contextualise the problems. Children applied real-world understanding to problem solving, including attribute identification, categorisation and classification skills. Intuitive and metarepresentational knowledge together with inductive and probabilistic reasoning was used to make sense of data, and beginning awareness of statistical variation and informal inference was visible.

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A cross-sectional survey was conducted, and the construct validity and reliability of the Brisbane Practice Environment Measure in an Australian sample of registered nurses were examined. Nurses were randomly selected from the database of an Australian nursing organization. The original 33 items of the Brisbane Practice Environment Measure were utilized to inform the psychometric properties using confirmatory factor analysis. The Cronbach's alpha was 0.938 for the total scale and ranged 0.657–0.887 for the subscales. A five-factor structure of the measure was confirmed, χ2 = 944.622, (P < 0.01), χ2/d.f. ratio = 2.845, Tucker Lewis Index 0.929, Root Mean Square Error = 0.061 and Comparative Fit Index = 0.906. The selected 28 items of the measure proved reliable and valid in measuring effects of the practice environment upon Australian nurses. The implications are that regular measurement of the practice environment using these 28 items might assist in the development of strategies which might improve job satisfaction and retention of registered nurses in Australia.