968 resultados para regression analysis


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STUDY OBJECTIVES: To evaluate the association between early stages of chronic kidney disease (CKD) and sleep disordered breathing (SDB), restless legs syndrome (RLS), and subjective and objective sleep quality (SQ). METHODS: Cross-sectional analysis of a general population-based cohort (HypnoLaus). 1,760 adults (862 men, 898 women; age 59.3 (± 11.4) y) underwent complete polysomnography at home. RESULTS: 8.2% of participants had mild CKD (stage 1-2, estimated glomerular filtration rate [eGFR] ≥ 60 mL/min/1.73 m(2) with albuminuria) and 7.8% moderate CKD (stage 3, eGFR 30-60 mL/min/1.73 m(2)). 37.3% of our sample had moderate-to-severe SDB (apnea-hypopnea index [AHI] ≥ 15/h) and 15.3% had severe SDB (AHI ≥ 30/h). SDB prevalence was positively associated with CKD stages and negatively with eGFR. In multivariate analysis, age, male sex, and body mass index were independently associated with SDB (all P < 0.001), but kidney function was not. The prevalence of RLS was 17.5%, without difference between CKD stages. Periodic leg movements index (PLMI) was independently associated with CKD stages. Subjective and objective SQ decreased and the use of sleep medication was more frequent with declining kidney function. Older age, female sex, and the severity of SDB were the strongest predictors of poor SQ in multivariate regression analysis but CKD stage was also independently associated with reduced objective SQ. CONCLUSIONS: Patients with early stages of CKD have impaired SQ, use more hypnotic drugs, and have an increased prevalence of SDB and PLM. After controlling for confounders, objective SQ and PLMI were still independently associated with declining kidney function.

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Health and inequalities in health among inhabitants of European cities are of major importance for European public health and there is great interest in how different health care systems in Europe perform in the reduction of health inequalities. However, evidence on the spatial distribution of cause-specific mortality across neighbourhoods of European cities is scarce. This study presents maps of avoidable mortality in European cities and analyses differences in avoidable mortality between neighbourhoods with different levels of deprivation. Methods: We determined the level of mortality from 14 avoidable causes of death for each neighbourhood of 15 large cities in different European regions. To address the problems associated with Standardised Mortality Ratios for small areas we smooth them using the Bayesian model proposed by Besag, York and Mollié. Ecological regression analysis was used to assess the association between social deprivation and mortality. Results: Mortality from avoidable causes of death is higher in deprived neighbourhoods and mortality rate ratios between areas with different levels of deprivation differ between gender and cities. In most cases rate ratios are lower among women. While Eastern and Southern European cities show higher levels of avoidable mortality, the association of mortality with social deprivation tends to be higher in Northern and lower in Southern Europe. Conclusions: There are marked differences in the level of avoidable mortality between neighbourhoods of European cities and the level of avoidable mortality is associated with social deprivation. There is no systematic difference in the magnitude of this association between European cities or regions. Spatial patterns of avoidable mortality across small city areas can point to possible local problems and specific strategies to reduce health inequality which is important for the development of urban areas and the well-being of their inhabitants

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This thesis investigates performance persistence among the equity funds investing in Russia during 2003-2007. Fund performance is measured using several methods including the Jensen alpha, the Fama-French 3- factor alpha, the Sharpe ratio and two of its variations. Moreover, we apply the Bayesian shrinkage estimation in performance measurement and evaluate its usefulness compared with the OLS 3-factor alphas. The pattern of performance persistence is analyzed using the Spearman rank correlation test, cross-sectional regression analysis and stacked return time series. Empirical results indicate that the Bayesian shrinkage estimates may provide better and more accurate estimates of fund performance compared with the OLS 3-factor alphas. Secondly, based on the results it seems that the degree of performance persistence is strongly related to length of the observation period. For the full sample period the results show strong signs of performance reversal whereas for the subperiod analysis the results indicate performance persistence during the most recent years.

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We sometimes vividly remember things that did not happen, a phenomenon with general relevance, not only in the courtroom. It is unclear to what extent individual differences in false memories are driven by anatomical differences in memory-relevant brain regions. Here we show in humans that microstructural properties of different white matter tracts as quantified using diffusion tensor imaging are strongly correlated with true and false memory retrieval. To investigate these hypotheses, we tested a large group of participants in a version of the Deese-Roediger-McDermott paradigm (recall and recognition) and subsequently obtained diffusion tensor images. A voxel-based whole-brain level linear regression analysis was performedto relatefractional anisotropyto indices oftrue andfalse memory recall and recognition. True memory was correlated to diffusion anisotropy in the inferior longitudinal fascicle, the major connective pathway of the medial temporal lobe, whereas a greater proneness to retrieve false items was related to the superior longitudinal fascicle connecting frontoparietal structures. Our results show that individual differences in white matter microstructure underlie true and false memory performance.

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[cat] Mentre que una creixent literatura que ha examinat la relació entre la renda i la despesa sanitària suggereix que els serveis sanitaris són un be de luxe (elasticitat renda superior a la unitat), aquesta conclusió es contínuament debatuda atesa l'heterogeneïtat dels resultats. Aquest article testa la hipòtesis dels serveis sanitaris com bens de luxe fent server anàlisi de meta- regressió, particularment analitzant l'existència de biaixos de selecció de publicació, precisió així com biaixos d'agregació. Els resultats apunten l'existència d'un biaix de publicació, robust independentment dels controls analitzats. Els biaixos de precisió i agregació semblen tenir un paper en la generació de les estimacions de l'elasticitat renda. Els nostres resultat suggereixen que l'elasticitat renda dels serveis sanitaris un cop corregir pels biaixos esmentat varien entre 0.26 i 0.84, però no podem rebutjar que la elasticitat renda es igual a la unitat en algunes estimacions de l'elasticitat corregides.

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[cat] Mentre que una creixent literatura que ha examinat la relació entre la renda i la despesa sanitària suggereix que els serveis sanitaris són un be de luxe (elasticitat renda superior a la unitat), aquesta conclusió es contínuament debatuda atesa l'heterogeneïtat dels resultats. Aquest article testa la hipòtesis dels serveis sanitaris com bens de luxe fent server anàlisi de meta- regressió, particularment analitzant l'existència de biaixos de selecció de publicació, precisió així com biaixos d'agregació. Els resultats apunten l'existència d'un biaix de publicació, robust independentment dels controls analitzats. Els biaixos de precisió i agregació semblen tenir un paper en la generació de les estimacions de l'elasticitat renda. Els nostres resultat suggereixen que l'elasticitat renda dels serveis sanitaris un cop corregir pels biaixos esmentat varien entre 0.26 i 0.84, però no podem rebutjar que la elasticitat renda es igual a la unitat en algunes estimacions de l'elasticitat corregides.

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Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

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The 2010 Green Paper on Audit Policy by the European Commission has explicitly questioned the sufficiency of audit rotation rules established by European Union Members to guarantee auditor independence. In addition, the Paper clearly states that more research is needed regarding the effects of long audit tenures on independence. In this article, we have replicated the research by Ruiz-Barbadillo, Gómez-Aguilar, and Biedma (2005) about the effects of audit firm tenure on independence with more updated data. However, unlike them, we have performed panel data estimations instead of pooled regression. Our approach allows for a better control of individual unobserved heterogeneity, thus reducing potential problems caused by omitted variable bias. While Ruiz-Barbadillo et al. reported an unexpected positive effect of tenure on the likelihood of audit qualifications, we do not show any significant effect of tenure on the opinion of the audit report. Our results are robust to various sensitivity analyses.

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We analyse volatility spillovers in EMU sovereign bond markets. First, we examine the unconditional patterns during the full sample (April 1999-January 2014) using a measure recently proposed by Diebold and Yılmaz (2012). Second, we make use of a dynamic analysis to evaluate net directional volatility spillovers for each of the eleven countries under study, and to determine whether core and peripheral markets present differences. Finally, we apply a panel analysis to empirically investigate the determinants of net directional spillovers of this kind.

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Tässä pro gradu -tutkielmassa tarkastellaan EU -jäsenyyden vaikutuksia itälaajentumisen myötä liittyneiden maiden maatalouteen ja sen tuottavuuteen. Maatalouden kehitys kuvaa kohdemaiden talouksien kehitystä. Uusien jäsenten kehitys taas vaikuttaa koko Euroopan unionin toimintaan ja sen asemaan maailmanmarkkinoilla. Tutkielman teoriaosuus esittelee tuottavuuden, yhteisen maatalouspolitiikan ja lineaarisen regressioanalyysin teoriaa. Empiriaosuudessa esitellään neljä kohdemaata ja tarkastellaan regressioanalyysien avulla sitä kuinka Euroopan unionin jäsenyys on vaikuttanut näiden maiden maataloussektoreiden tuottavuuteen.

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This thesis studies capital structure of Finnish small and medium sized enterprises. The specific object of the study is to test whether financial constraints have an effect on capital structure. In addition influences of several other factors were studied. Capital structure determinants are formulated based on three capital structure theories. The tradeoff theory and the agency theory concentrate on the search of optimal capital structure. The pecking order theory concerns favouring on financing source over another. The data of this study consists of financial statement data and results of corporate questionnaire. Regression analysis was used to find out the effects of several determinants. Regression models were formed based on the presented theories. Short and long term debt ratios were considered separately. The metrics of financially constrained firms was included in all models. It was found that financial constrains have a negative and significant effect to short term debt ratios. The effect was negative also to long term debt ratio but not statistically significant. Other considerable factors that influenced debt ratios were fixed assets, age, profitability, single owner and sufficiency of internal financing.

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The Thesis is dedicated to development of an operative tool to support decision making in after spot trading on the Nordic electricity market. The basics of the Nordic electricity market, trading mechanisms on the spot and after spot markets are presented in the Thesis. Mathematical equations that describe electricity balance condition in the power system are offered. The main driving factors that impact deviation of actual electricity balance from the scheduled one (object) in the power system have been explored and mathematically defined. The behavioral model of the object and principal trends in change of state of the object under an impact of the driving factors are determined with the help of regression analysis made in Microsoft Office Excel. The behavioral model gives an indication for the total regulation volume (Elbas trades volume, volume of regulation market, balance power) for a certain hour that serves as the base input in estimating prices on the after spot markets. Proposals for development of methodologies of forecasting the after spot electricity prices are offered.

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BACKGROUND: The association between obesity and back pain has mainly been studied in high-income settings with inconclusive results, and data from older populations and developing countries are scarce. The aim of this study was to assess this association in nine countries in Asia, Africa, Europe, and Latin America among older adults using nationally-representative data. METHODS: Data on 42116 individuals ≥50 years who participated in the Collaborative Research on Ageing in Europe (COURAGE) study conducted in Finland, Poland, and Spain in 2011-2012, and the World Health Organization's Study on Global Ageing and Adult Health (SAGE) conducted in China, Ghana, India, Mexico, Russia, and South Africa in 2007-2010 were analysed. Information on measured height and weight available in the two datasets was used to calculate Body Mass Index (BMI). Self-reported back pain occurring in the past 30 days was the outcome. Multivariable logistic regression analysis was used to assess the association between BMI and back pain. RESULTS: The prevalence of back pain ranged from 21.5% (China) to 57.5% (Poland). In the multivariable analysis, compared to BMI 18.5-24.9 kg/m(2), significantly higher odds for back pain were observed for BMI ≥35 kg/m(2) in Finland (OR 3.33), Russia (OR 2.20), Poland (OR 2.03), Spain (OR 1.56), and South Africa (OR 1.48); BMI 30.0-34.0 kg/m(2) in Russia (OR 2.76), South Africa (OR 1.51), and Poland (OR 1.47); and BMI 25.0-29.9 kg/m(2) in Russia (OR 1.51) and Poland (OR 1.40). No significant associations were found in the other countries. CONCLUSIONS: The strength of the association between obesity and back pain may vary by country. Future studies are needed to determine the factors contributing to differences in the associations observed.

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Eri tieteenalojen tutkijat ovat kiistelleet jo yli vuosisadan ajan ratiomuodossa olevien muuttujien käytön vaikutuksista korrelaatio- ja regressioanalyysien tuloksiin ja niiden oikeaan tulkintaan. Strategiatutkimuksen piirissä aiheeseen ei ole kuitenkaan kiinnitetty suuresti huomiota. Tämä on yllättävää, sillä ratiomuuttujat ovat hyvin yleisesti käytettyjä empiirisen strategiatutkimuksen piirissä. Tässä työssä luodaan katsaus ratiomuuttujien ympärillä käytyyn debattiin. Lisäksi selvitetään artikkelikatsauksen avulla niiden käytön yleisyyttä nykypäivän strategiatutkimuksessa. Työssä tutkitaan Monte Carlo –simulaatioiden avulla ratiomuuttujien ominaisuuksien vaikutuksia korrelaatio- ja regressioanalyysin tuloksiin erityisesti yhteisen nimittäjän tapauksissa.

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Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.