100 resultados para REGRESSION THEOREM


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This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Introduction: This systematic review and meta-regression analysis aimed to calculate a combined prevalence estimate and evaluate the prevalence of different Treponema species in primary and secondary endodontic infections, including symptomatic and asymptomatic eases. Methods: The MEDLINE/PubMed, Embase, Scielo, Web of Knowledge, and Scopus data-bases were searched without starting date restriction up to and including March 2014. Only reports in English were included. The selected literature was reviewed by 2 authors and classified as suitable or not to be included in this review. Lists were compared, and, in case of disagreements, decisions were made after a discussion based on inclusion and exclusion criteria. A pooled prevalence of Treponema species in endodontic infections was estimated. Additionally, a meta-regression analysis was performed. Results: Among the 265 articles identified in the initial search, only 51 were included in the final analysis. The studies were classified into 2 different groups according to the type of endodontic infection and whether it was an exclusively primary/secondary study (n = 36) or a primary/secondary comparison (n = 15). The pooled prevalence of Treponema species was 41.5% (95% confidence interval, 35.9-47.0). In the multivariate model of meta-regression analysis, primary endodontic infections (P < .001), acute apical abscess, symptomatic apical periodontitis (P < .001), and concomitant presence of 2 or more species (P = .028) explained the heterogeneity regarding the prevalence rates of Treponema species. Conclusions: Our findings suggest that Treponema species are important pathogens involved in endodontic infections, particularly in cases of primary and acute infections.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The anesthesia-related cardiac arrest (CA) rate is a quality indicator to improve patient safety in the perioperative period. A systematic review with meta-analysis of the worldwide literature related to anesthesia-related CA rate has not yet been performed.This study aimed to analyze global data on anesthesia-related and perioperative CA rates according to country's Human Development Index (HDI) and by time. In addition, we compared the anesthesia-related and perioperative CA rates in low- and high-income countries in 2 time periods.A systematic review was performed using electronic databases to identify studies in which patients underwent anesthesia with anesthesia-related and/or perioperative CA rates. Meta-regression and proportional meta-analysis were performed with 95% confidence intervals (CIs) to evaluate global data on anesthesia-related and perioperative CA rates according to country's HDI and by time, and to compare the anesthesia-related and perioperative CA rates by country's HDI status (low HDI vs high HDI) and by time period (pre-1990s vs 1990s-2010s), respectively.Fifty-three studies from 21 countries assessing 11.9 million anesthetic administrations were included. Meta-regression showed that anesthesia-related (slope: -3.5729; 95% CI: -6.6306 to -0.5152; P = 0.024) and perioperative (slope: -2.4071; 95% CI: -4.0482 to -0.7659; P = 0.005) CA rates decreased with increasing HDI, but not with time. Meta-analysis showed per 10,000 anesthetics that anesthesia-related and perioperative CA rates declined in high HDI (2.3 [95% CI: 1.2-3.7] before the 1990s to 0.7 [95% CI: 0.5-1.0] in the 1990s-2010s, P < 0.001; and 8.1 [95% CI: 5.1-11.9] before the 1990s to 6.2 [95% CI: 5.1-7.4] in the 1990s-2010s, P < 0.001, respectively). In low-HDI countries, anesthesia-related CA rates did not alter significantly (9.2 [95% CI: 2.0-21.7] before the 1990s to 4.5 [95% CI: 2.4-7.2] in the 1990s-2010s, P = 0.14), whereas perioperative CA rates increased significantly (16.4 [95% CI: 1.5-47.1] before the 1990s to 19.9 [95% CI: 10.9-31.7] in the 1990s-2010s, P = 0.03).Both anesthesia-related and perioperative CA rates decrease with increasing HDI but not with time. There is a clear and consistent reduction in anesthesia-related and perioperative CA rates in high-HDI countries, but an increase in perioperative CA rates without significant alteration in the anesthesia-related CA rates in low-HDI countries comparing the 2 time periods.

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The new result presented here is a theorem involving series in the three-parameter Mittag-Le er function. As a by-product, we recover some known results and discuss corollaries. As an application, we obtain the solution of a fractional di erential equation associated with a RLC electrical circuit in a closed form, in terms of the two-parameter Mittag-Le er function.

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Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.