900 resultados para meta-regression analysis
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This research project provides a scientifically robust approach for assessing the resilience of water supply systems, which are critical infrastructure, to impacts of climate change and population growth. An approach for the identification of trigger points that allows timely and appropriate management actions to be taken to avoid catastrophic system failure is an important outcome of this project. In the current absence of a formal method to evaluate the resilience of a water supply system, the approach developed in this study was based on the characterisation of resilience of a water supply system to a range of surrogate measures. Accordingly, a set of indicators are proposed to evaluate system behaviour and logistic regression analysis was used to assess system behaviour under predicted rainfall, storage and demand conditions.
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Background Anxiety disorders and major depressive disorder (MDD) are common and disabling mental disorders. This paper aims to test the hypothesis that common mental disorders have become more prevalent over the past two decades. Methods We conducted a systematic review of prevalence, remission, duration, and excess mortality studies for anxiety disorders and MDD and then used a Bayesian meta-regression approach to estimate point prevalence for 1990, 2005, and 2010. We also conducted a post-hoc search for studies that used the General Health Questionnaire (GHQ) as a measure of psychological distress and tested for trends to present a qualitative comparison of study findings. Results This study found no evidence for an increased prevalence of anxiety disorders or MDD. While the crude number of cases increased by 36%, this was explained by population growth and changing age structures. Point prevalence of anxiety disorders was estimated at 3.8% (3.6-4.1%) in 1990 and 4.0% (3.7-4.2%) in 2010. The prevalence of MDD was unchanged at 4.4% in 1990 (4.2-4.7%) and 2010 (4.1-4.7%). However, 8 of the 11 GHQ studies found a significant increase in psychological distress over time. Conclusions The perceived "epidemic" of common mental disorders is most likely explained by the increasing numbers of affected patients driven by increasing population sizes. Additional factors that may explain this perception include the higher rates of psychological distress as measured using symptom checklists, greater public awareness, and the use of terms such as anxiety and depression in a context where they do not represent clinical disorders.
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Anxiety disorders are increasingly acknowledged as a global health issue however an accurate picture of prevalence across populations is lacking. Empirical data are incomplete and inconsistent so alternate means of estimating prevalence are required to inform estimates for the new Global Burden of Disease Study 2010. We used a Bayesian meta-regression approach which included empirical epidemiological data, expert prior information, study covariates and population characteristics. Reported are global and regional point prevalence for anxiety disorders in 2010. Point prevalence of anxiety disorders differed by up to three-fold across world regions, ranging between 2.1% (1.8-2.5%) in East Asia and 6.1% (5.1-7.4%) in North Africa/Middle East. Anxiety was more common in Latin America; high income regions; and regions with a history of recent conflict. There was considerable uncertainty around estimates, particularly for regions where no data were available. Future research is required to examine whether variations in regional distributions of anxiety disorders are substantive differences or an artefact of cultural or methodological differences. This is a particular imperative where anxiety is consistently reported to be less common, and where it appears to be elevated, but uncertainty prevents the reporting of conclusive estimates.
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Aim Estimate the prevalence of cannabis dependence and its contribution to the global burden of disease. Methods Systematic reviews of epidemiological data on cannabis dependence (1990-2008) were conducted in line with PRISMA and meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Culling and data extraction followed protocols, with cross-checking and consistency checks. DisMod-MR, the latest version of generic disease modelling system, redesigned as a Bayesian meta-regression tool, imputed prevalence by age, year and sex for 187 countries and 21 regions. The disability weight associated with cannabis dependence was estimated through population surveys and multiplied by prevalence data to calculate the years of life lived with disability (YLDs) and disability-adjusted life years (DALYs). YLDs and DALYs attributed to regular cannabis use as a risk factor for schizophrenia were also estimated. Results There were an estimated 13.1 million cannabis dependent people globally in 2010 (point prevalence0.19% (95% uncertainty: 0.17-0.21%)). Prevalence peaked between 20-24 yrs, was higher in males (0.23% (0.2-0.27%)) than females (0.14% (0.12-0.16%)) and in high income regions. Cannabis dependence accounted for 2 million DALYs globally (0.08%; 0.05-0.12%) in 2010; a 22% increase in crude DALYs since 1990 largely due to population growth. Countries with statistically higher age-standardised DALY rates included the United States, Canada, Australia, New Zealand and Western European countries such as the United Kingdom; those with lower DALY rates were from Sub-Saharan Africa-West and Latin America. Regular cannabis use as a risk factor for schizophrenia accounted for an estimated 7,000 DALYs globally. Conclusion Cannabis dependence is a disorder primarily experienced by young adults, especially in higher income countries. It has not been shown to increase mortality as opioid and other forms of illicit drug dependence do. Our estimates suggest that cannabis use as a risk factor for schizophrenia is not a major contributor to population-level disease burden.
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Background Summarizing the epidemiology of major depressive disorder (MDD) at a global level is complicated by significant heterogeneity in the data. The aim of this study is to present a global summary of the prevalence and incidence of MDD, accounting for sources of bias, and dealing with heterogeneity. Findings are informing MDD burden quantification in the Global Burden of Disease (GBD) 2010 Study. Method A systematic review of prevalence and incidence of MDD was undertaken. Electronic databases Medline, PsycINFO and EMBASE were searched. Community-representative studies adhering to suitable diagnostic nomenclature were included. A meta-regression was conducted to explore sources of heterogeneity in prevalence and guide the stratification of data in a meta-analysis. Results The literature search identified 116 prevalence and four incidence studies. Prevalence period, sex, year of study, depression subtype, survey instrument, age and region were significant determinants of prevalence, explaining 57.7% of the variability between studies. The global point prevalence of MDD, adjusting for methodological differences, was 4.7% (4.4–5.0%). The pooled annual incidence was 3.0% (2.4–3.8%), clearly at odds with the pooled prevalence estimates and the previously reported average duration of 30 weeks for an episode of MDD. Conclusions Our findings provide a comprehensive and up-to-date profile of the prevalence of MDD globally. Region and study methodology influenced the prevalence of MDD. This needs to be considered in the GBD 2010 study and in investigations into the ecological determinants of MDD. Good-quality estimates from low-/middle-income countries were sparse. More accurate data on incidence are also required.
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Elevated levels of fungi in indoor environments have been linked with mould/moisture damage in building structures. However, there is a lack of information about “normal” concentrations and flora as well as guidelines of viable fungi in the school environment in different climatic conditions. We have reviewed existing guidelines for indoor fungi and the current knowledge of the concentrations and flora of viable fungi in different climatic areas, the impact of the local factors on concentrations and flora of viable fungi in school environments. Meta-regression was performed to estimate the average behaviour for each analysis of interest, showing wide variation in the mean concentrations in outdoor and indoor school environments (range: 101-103 cfu/m3). These concentrations were significantly higher for both outdoors and indoors in the moderate than in the continental climatic area, showing that the climatic condition was a determinant for the concentrations of airborne viable fungi. The most common fungal species both in the moderate and continental area were Cladosporium spp. and Penicillium spp. The suggested few quantitative guidelines for indoor air viable fungi for school buildings are much lower than for residential areas. This review provides a synthesis, which can be used to guide the interpretation of the fungi measurements results and help to find indications of mould/moisture in school building structures.
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Long-term systematic population monitoring data sets are rare but are essential in identifying changes in species abundance. In contrast, community groups and natural history organizations have collected many species lists. These represent a large, untapped source of information on changes in abundance but are generally considered of little value. The major problem with using species lists to detect population changes is that the amount of effort used to obtain the list is often uncontrolled and usually unknown. It has been suggested that using the number of species on the list, the "list length," can be a measure of effort. This paper significantly extends the utility of Franklin's approach using Bayesian logistic regression. We demonstrate the value of List Length Analysis to model changes in species prevalence (i.e., the proportion of lists on which the species occurs) using bird lists collected by a local bird club over 40 years around Brisbane, southeast Queensland, Australia. We estimate the magnitude and certainty of change for 269 bird species and calculate the probabilities that there have been declines and increases of given magnitudes. List Length Analysis confirmed suspected species declines and increases. This method is an important complement to systematically designed intensive monitoring schemes and provides a means of utilizing data that may otherwise be deemed useless. The results of List Length Analysis can be used for targeting species of conservation concern for listing purposes or for more intensive monitoring. While Bayesian methods are not essential for List Length Analysis, they can offer more flexibility in interrogating the data and are able to provide a range of parameters that are easy to interpret and can facilitate conservation listing and prioritization. © 2010 by the Ecological Society of America.
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Several clinical studies suggest the involvement of premature ageing processes in chronic obstructive pulmonary disease (COPD). Using an epidemiological approach, we studied whether accelerated ageing indicated by telomere length, a marker of biological age, is associated with COPD and asthma, and whether intrinsic age-related processes contribute to the interindividual variability of lung function. Our meta-analysis of 14 studies included 934 COPD cases with 15 846 controls defined according to the Global Lungs Initiative (GLI) criteria (or 1189 COPD cases according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria), 2834 asthma cases with 28 195 controls, and spirometric parameters (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC) of 12 595 individuals. Associations with telomere length were tested by linear regression, adjusting for age, sex and smoking status. We observed negative associations between telomere length and asthma (β= −0.0452, p=0.024) as well as COPD (β= −0.0982, p=0.001), with associations being stronger and more significant when using GLI criteria than those of GOLD. In both diseases, effects were stronger in females than males. The investigation of spirometric indices showed positive associations between telomere length and FEV1 (p=1.07×10−7), FVC (p=2.07×10−5), and FEV1/FVC (p=5.27×10−3). The effect was somewhat weaker in apparently healthy subjects than in COPD or asthma patients. Our results provide indirect evidence for the hypothesis that cellular senescence may contribute to the pathogenesis of COPD and asthma, and that lung function may reflect biological ageing primarily due to intrinsic processes, which are likely to be aggravated in lung diseases.
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Objectives: Recent association studies by the Australo-Anglo-American Spondyloarthritis Consortium (TASC) in Caucasian European populations from Australia, North America and the UK have identified a number of genes as being associated with ankylosing spondylitis (AS). A candidate gene study in a Han Chinese population was performed based on these findings to identify associated genes in this population. Methods: A case-control study was performed in a Han Chinese population of patients with AS (n=775) and controls (n=1587) from Shanghai and Nanjing. All patients met the modified New York criteria for AS. The cases and controls were genotyped for 115 single nucleotide polymorphisms (SNPs) tagging IL23R, ERAP1, STAT3, JAK2, TNFRSF1A and TRADD, as well as other confirmation SNPs from the TASC study, using the Sequenom iPlex and the ABI OpenArray platforms. Statistical analysis of genotyped SNPs was performed using the Cochran - Armitage test for trend and meta-analysis was performed using METAL. SNPs in AS-associated genes in this study were then imputed using MaCH, and association with AS tested by logistic regression. Results: SNPs in TNFRSF1A (rs4149577, p=8.2×10-4), STAT3 (rs2293152, p=0.0015; rs1053005, p=0.017) and ERAP1 (rs27038, p=0.0091; rs27037, p=0.0092) were significantly associated with AS in Han Chinese. Association was also observed between AS and the intergenic region 2p15 (rs10865331, p=0.023). The lack of association between AS and IL23R in Han Chinese was confirmed (all SNPs p>0.1). Conclusions: The study results demonstrate for the first time that genetic polymorphisms in STAT3, TNFRSF1A and 2p15 are associated with AS in Han Chinese, suggesting common pathogenic mechanisms for the disease in Chinese and Caucasian European populations. Furthermore, previous findings demonstrating that ERAP1, but not IL23R, is associated with AS in Chinese patients were confirmed.
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Background The number of citations received by an article is considered as an objective marker judging the importance and the quality of the research work. The present study aims to study the determinants of citations for research articles published by Sri Lankan authors. Methods Papers were selectively retrieved from the SciVerse Scopus® (Elsevier Properties S.A, USA) database for 10 years from 1st January 1997 to 31st December 2006, of which 50% were selected for inclusion by simple random sampling. The primary outcome measure was citation rate (defined as the number of citations during the 2 subsequent years after publication). Citation data was collected using the SciVerse Scopus® Citation Analyzer and self citations were excluded. A linear regression analysis was performed with ‘number of citations’ as the continuous dependent variable and other independent variables. Result The number of publications has steadily increased during the period of study. Over three quarter of papers were published in international journals. More than half of publications were research studies (55.3%), and most of the research studies were descriptive cross-sectional studies (27.1%). The mean number of citations within 2 years of publication was 1.7 and 52.1% of papers were not cited within the first two years of publication. The mean number of citations for collaborative studies (2.74) was significantly higher than that of non-collaborative studies (0.66). The mean number of citations did not significantly change depending on whether the publication had a positive result (2.08) or not (2.92) and was also not influenced by the presence (2.30) or absence (1.99) of the main study conclusion in the title of the article. In the linear regression model, the journal rank, number of authors, conducting the study abroad, being a research study or systematic review/meta-analysis and having regional and/or international collaboration all significantly increased the number of citations. Conclusion The journal rank, number of authors, conducting the study abroad, being a research study or systematic review/meta-analysis and having regional and/or international collaboration all significantly increased the number of citations. However, the presence of a positive result in the study did not influence the citation rate.
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This paper proposes a linear quantile regression analysis method for longitudinal data that combines the between- and within-subject estimating functions, which incorporates the correlations between repeated measurements. Therefore, the proposed method results in more efficient parameter estimation relative to the estimating functions based on an independence working model. To reduce computational burdens, the induced smoothing method is introduced to obtain parameter estimates and their variances. Under some regularity conditions, the estimators derived by the induced smoothing method are consistent and have asymptotically normal distributions. A number of simulation studies are carried out to evaluate the performance of the proposed method. The results indicate that the efficiency gain for the proposed method is substantial especially when strong within correlations exist. Finally, a dataset from the audiology growth research is used to illustrate the proposed methodology.
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- Purpose Communication of risk management practices are a critical component of good corporate governance. Research to date has been of little benefit in informing regulators internationally. This paper seeks to contribute to the literature by investigating how listed Australian companies in a setting where disclosures are explicitly required by the ASX corporate governance framework, disclose risk management (RM) information in the corporate governance statements within annual reports. - Design/methodology/approach To address our study’s research questions and related hypotheses, we examine the top 300 ASX-listed companies by market capitalisation at 30 June 2010. For these firms, we identify, code and categorise RM disclosures made in the annual reports according to the disclosure categories specified in Australian Stock Exchange Corporate Governance Principles and Recommendations (ASX CGPR). The derived data is then examined using a comprehensive approach comprising thematic content analysis and regression analysis. - Findings The results indicate widespread divergence in disclosure practices and low conformance with the Principle 7 of the ASX CGPR. This result suggests that companies are not disclosing all ‘material business risks’ possibly due to ignorance at the board level, or due to the intentional withholding of sensitive information from financial statement users. The findings also show mixed results across the factors expected to influence disclosure behaviour. Notably, the presence of a risk committee (RC) (in particular, a standalone RC) and technology committee (TC) are found to be associated with improved levels of disclosure. we do not find evidence that company risk measures (as proxied by equity beta and the market-to-book ratio) are significantly associated with greater levels of RM disclosure. Also, contrary to common findings in the disclosure literature, factors such as board independence and expertise, audit committee independence, and the usage of a Big-4 auditor do not seem to impact the level of RM disclosure in the Australian context. - Research limitation/implications The study is limited by the sample and study period selection as the RM disclosures of only the largest (top 300) ASX firms are examined for the fiscal year 2010. Thus, the finding may not be generalisable to smaller firms, or earlier/later years. Also, the findings may have limited applicability in other jurisdictions with different regulatory environments. - Practical implications The study’s findings suggest that insufficient attention has been applied to RM disclosures by listed companies in Australia. These results suggest that the RM disclosures practices observed in the Australian setting may not be meeting the objectives of regulators and the needs of stakeholders. - Originality/value Despite the importance of risk management communication, it is unclear whether disclosures in annual financial reports achieve this communication. The Australian setting provides an ideal environment to examine the nature and extent of risk management communication as the Australian Securities Exchange (ASX) has recommended risk management disclosures follow Principle 7 of its principle-based governance rules since 2007.
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Longitudinal studies of entrepreneurial career development are rare, and current knowledge of self-employment patterns and their relationships with individual difference characteristics is limited. In this study, the authors analyzed employment data from a subsample of 514 participants from the German Socio-Economic Panel study (1984–2008). Results of an optimal matching analysis indicated that a continuous self-employment pattern could be distinguished from four alternative employment patterns (change from employment to self-employment, full-time employees, part-time employees, and farmers). Results of a multinomial logistic regression analysis showed that certain socio-demographic characteristics (i.e., age and gender) and personality characteristics (i.e., conscientiousness and risk-taking propensity) were related to the likelihood of following a continuous self-employment pattern compared to the other employment patterns. Implications for future research on entrepreneurial career development are discussed.
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The focus of this study is on statistical analysis of categorical responses, where the response values are dependent of each other. The most typical example of this kind of dependence is when repeated responses have been obtained from the same study unit. For example, in Paper I, the response of interest is the pneumococcal nasopharengyal carriage (yes/no) on 329 children. For each child, the carriage is measured nine times during the first 18 months of life, and thus repeated respones on each child cannot be assumed independent of each other. In the case of the above example, the interest typically lies in the carriage prevalence, and whether different risk factors affect the prevalence. Regression analysis is the established method for studying the effects of risk factors. In order to make correct inferences from the regression model, the associations between repeated responses need to be taken into account. The analysis of repeated categorical responses typically focus on regression modelling. However, further insights can also be gained by investigating the structure of the association. The central theme in this study is on the development of joint regression and association models. The analysis of repeated, or otherwise clustered, categorical responses is computationally difficult. Likelihood-based inference is often feasible only when the number of repeated responses for each study unit is small. In Paper IV, an algorithm is presented, which substantially facilitates maximum likelihood fitting, especially when the number of repeated responses increase. In addition, a notable result arising from this work is the freely available software for likelihood-based estimation of clustered categorical responses.
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In this Thesis, we develop theory and methods for computational data analysis. The problems in data analysis are approached from three perspectives: statistical learning theory, the Bayesian framework, and the information-theoretic minimum description length (MDL) principle. Contributions in statistical learning theory address the possibility of generalization to unseen cases, and regression analysis with partially observed data with an application to mobile device positioning. In the second part of the Thesis, we discuss so called Bayesian network classifiers, and show that they are closely related to logistic regression models. In the final part, we apply the MDL principle to tracing the history of old manuscripts, and to noise reduction in digital signals.