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Indicadores clínicos e pré-hospitalares de sobrevivência no trauma fechado: uma análise multivariada; Clinical and prehospital survival indicators in blunt trauma: a multivariate analysis; Indicadores clínicos y prehospitalarios de supervivencia al trauma cerrado: un análisis multivariado

MALVESTIO, Marisa Aparecida Amaro; SOUSA, Regina Marcia Cardoso de
Fonte: Universidade de São Paulo, Escola de Enfermagem Publicador: Universidade de São Paulo, Escola de Enfermagem
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.92%
O objetivo do estudo foi identificar os indicadores clínicos e pré-hospitalares associados à sobrevivência de vítimas de trauma fechado. Foram utilizadas a análise de sobrevivência de Kaplan Meier, e de Riscos Proporcionais de Cox, para analisar a associação de 33 variáveis ao óbito precoce e tardio, propondo modelos multivariados. Os modelos finais até 48h pós-trauma evidenciaram altos coeficientes de risco promovidos pelas lesões abdominais, Injury Severity Score >25, procedimentos respiratórios avançados e compressões torácicas pré-hospitalares. No modelo até 7 dias, a pressão arterial sistólica na cena do acidente, se menor de 75mmHg, foi associada a maior risco de óbito e se ausente, foi associada ao mais elevado risco de óbito após 7 dias. A reposição de volume pré-hospitalar apresentou efeito protetor em todos os períodos. Os resultados sugerem que a magnitude da hipoxemia e da instabilidade hemodinâmica diante da hemorragia, influenciaram de forma significante o óbito precoce e tardio desse grupo de vítimas.; The aim of the study was to identify the clinical and prehospital indicators associated to the survival of blunt trauma victims. The Kaplan Meier survival analysis and the Cox proportional hazards model were used to analyze the association of 33 variables to early and late death...

Covariates of high-risk human papillomavirus (HPV) infections are distinct for incident CIN1, CIN2 and CIN3 as disclosed by competing-risks regression models

Syrjanen, K.; Shabalova, I.; Sarian, L.; Naud, P.; Longatto-Filho, A.; Derchain, S.; Kozachenko, V.; Zakharchenko, S.; Roteli-Martins, C.; Nerovjna, R.; Kljukina, L.; Tatti, S.; Branovskaja, M.; Branca, M.; Grunjberga, V.; Erzen, M.; Juschenko, A.; Hammes
Fonte: I R O G CANADA, INC; MONTREAL Publicador: I R O G CANADA, INC; MONTREAL
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.95%
Background: In addition to the oncogenic human papillomavirus (HPV), several cofactors are needed in cervical carcinogenesis, but whether the HPV covariates associated with incident i) CIN1 are different from those of incident ii) CIN2 and iii) CIN3 needs further assessment. Objectives: To gain further insights into the true biological differences between CIN1, CIN2 and CIN3, we assessed HPV covariates associated with incident CIN1, CIN2, and CIN3. Study Design and Methods: HPV covariates associated with progression to CIN1, CIN2 and CIN3 were analysed in the combined cohort of the NIS (n = 3,187) and LAMS study (n = 12,114), using competing-risks regression models (in panel data) for baseline HR-HPV-positive women (n = 1,105), who represent a sub-cohort of all 1,865 women prospectively followed-up in these two studies. Results: Altogether, 90 (4.8%), 39 (2.1%) and 14 (1.4%) cases progressed to CIN1, CIN2, and CIN3, respectively. Among these baseline HR-HPV-positive women, the risk profiles of incident GIN I, CIN2 and CIN3 were unique in that completely different HPV covariates were associated with progression to CIN1, CIN2 and CIN3, irrespective which categories (non-progression, CIN1, CIN2, CIN3 or all) were used as competing-risks events in univariate and multivariate models. Conclusions: These data confirm our previous analysis based on multinomial regression models implicating that distinct covariates of HR-HPV are associated with progression to CIN1...

Avaliação de modelos geoestatísticos multivariados; Evaluation of Multivariate Geostatistic Models

Righetto, Ana Julia
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 17/12/2012 Português
Relevância na Pesquisa
46.13%
Questões centrais em diversas áreas do conhecimento como ciências ambientais, geologia, agronomia, dentre outras, envolvem a compreensão da distribuição espacial de processos a partir de dados espacialmente referenciados. Os interesses de pesquisa podem estar na descrição espacial de duas ou mais variáveis e, desta forma, tem-se dois ou mais atributos para modelar. Modelos multivariados são propostos para o estudo se há evidências e/ou explicações contextuais de que os processos não são independentes. Diferentes modelos propostos na literatura foram avaliados e comparados ao modelo Matérn multivariado, recentemente proposto na literatura. Foram considerados o modelo linear de corregionalização, o modelo bivariado gaussiano de componente comum e um modelo bayesiano de regressão espacial. Estes modelos foram ajustados e utilizados para predição espacial geoestatística (krigagem) em um conjunto de dados com duas variáveis climáticas no qual uma parte dos dados foi separada para avaliação das predições. Além disso, foi realizado um estudo de simulação para avaliar a estimação e predição sob o modelo Matérn multivariado.; Key issues in a diversity of subject areas such as environmental sciences, geology...

Forecasting Multivariate Time Series under Present-Value-Model Short- and Long-run Co-movement Restrictions

Guillén, Osmani; Hecq, Alain; Issler, João Victor; Saraiva, Diogo
Fonte: Escola de Pós-Graduação em Economia da FGV Publicador: Escola de Pós-Graduação em Economia da FGV
Tipo: Relatório
Português
Relevância na Pesquisa
55.95%
This paper has two original contributions. First, we show that the present value model (PVM hereafter), which has a wide application in macroeconomics and fi nance, entails common cyclical feature restrictions in the dynamics of the vector error-correction representation (Vahid and Engle, 1993); something that has been already investigated in that VECM context by Johansen and Swensen (1999, 2011) but has not been discussed before with this new emphasis. We also provide the present value reduced rank constraints to be tested within the log-linear model. Our second contribution relates to forecasting time series that are subject to those long and short-run reduced rank restrictions. The reason why appropriate common cyclical feature restrictions might improve forecasting is because it finds natural exclusion restrictions preventing the estimation of useless parameters, which would otherwise contribute to the increase of forecast variance with no expected reduction in bias. We applied the techniques discussed in this paper to data known to be subject to present value restrictions, i.e. the online series maintained and up- dated by Shiller. We focus on three different data sets. The fi rst includes the levels of interest rates with long and short maturities...

Forecasting Multivariate Time Series under Present-Value-Model Short- and Long-run Co-movement Restrictions

Teixeira de Carvalho Guillén, Osmani; Hecq, Alain; Victor Issler, João; Saraiva, Diogo
Fonte: Escola de Pós-Graduação em Economia da FGV Publicador: Escola de Pós-Graduação em Economia da FGV
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
56.08%
Using a sequence of nested multivariate models that are VAR-based, we discuss different layers of restrictions imposed by present-value models (PVM hereafter) on the VAR in levels for series that are subject to present-value restrictions. Our focus is novel - we are interested in the short-run restrictions entailed by PVMs (Vahid and Engle, 1993, 1997) and their implications for forecasting. Using a well-known database, kept by Robert Shiller, we implement a forecasting competition that imposes different layers of PVM restrictions. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to the unrestricted VAR. Moreover, imposing short-run restrictions produces forecast winners 70% of the time for the target variables of PVMs and 63.33% of the time when all variables in the system are considered.

Multivariate models for correlated count data

Rodrigues-Motta, Mariana; Pinheiro, Hildete P.; Martins, Eduardo G.; Araújo, Márcio S.; dos Reis, Sérgio F.
Fonte: Universidade Estadual Paulista Publicador: Universidade Estadual Paulista
Tipo: Artigo de Revista Científica Formato: 1586-1596
Português
Relevância na Pesquisa
45.87%
In this study, we deal with the problem of overdispersion beyond extra zeros for a collection of counts that can be correlated. Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial distributions have been considered. First, we propose a multivariate count model in which all counts follow the same distribution and are correlated. Then we extend this model in a sense that correlated counts may follow different distributions. To accommodate correlation among counts, we have considered correlated random effects for each individual in the mean structure, thus inducing dependency among common observations to an individual. The method is applied to real data to investigate variation in food resources use in a species of marsupial in a locality of the Brazilian Cerrado biome. © 2013 Copyright Taylor and Francis Group, LLC.

Covariates of high-risk human papillomavirus (HPV) infections are distinct for incident CIN1, CIN2 and CIN3 as disclosed by competing-risks regression models

Syrjanen, K.; Shabalova, I.; Sarian, L.; Naud, P.; Longatto-Filho, A.; Derchain, S.; Kozachenko, V.; Zakharchenko, S.; Roteli-Martins, C.; Nerovjna, R.; Kljukina, L.; Tatti, S.; Branovskaja, M.; Branca, M.; Grunjberga, V.; Erzen, M.; Juschenko, A.; Hammes
Fonte: I R O G Canada, Inc; Montreal Publicador: I R O G Canada, Inc; Montreal
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.95%
Background: In addition to the oncogenic human papillomavirus (HPV), several cofactors are needed in cervical carcinogenesis, but whether the HPV covariates associated with incident i) CIN1 are different from those of incident ii) CIN2 and iii) CIN3 needs further assessment. Objectives: To gain further insights into the true biological differences between CIN1, CIN2 and CIN3, we assessed HPV covariates associated with incident CIN1, CIN2, and CIN3. Study Design and Methods: HPV covariates associated with progression to CIN1, CIN2 and CIN3 were analysed in the combined cohort of the NIS (n = 3,187) and LAMS study (n = 12,114), using competing-risks regression models (in panel data) for baseline HR-HPV-positive women (n = 1,105), who represent a sub-cohort of all 1,865 women prospectively followed-up in these two studies. Results: Altogether, 90 (4.8%), 39 (2.1%) and 14 (1.4%) cases progressed to CIN1, CIN2, and CIN3, respectively. Among these baseline HR-HPV-positive women, the risk profiles of incident GIN I, CIN2 and CIN3 were unique in that completely different HPV covariates were associated with progression to CIN1, CIN2 and CIN3, irrespective which categories (non-progression, CIN1, CIN2, CIN3 or all) were used as competing-risks events in univariate and multivariate models. Conclusions: These data confirm our previous analysis based on multinomial regression models implicating that distinct covariates of HR-HPV are associated with progression to CIN1...

Profile of health-related quality of life outcomes after liver transplantation: univariate effects and multivariate models

Russell, R. T.; Feurer, I. D.; Wisawatapnimit, P.; Lillie, E. S.; Castaldo, E. T.; Wright Pinson, C.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em //2008 Português
Relevância na Pesquisa
45.92%
Aim. To test the effects of pre- and post-transplant clinical covariates on post-transplant health-related quality of life (HRQOL) score profiles in liver transplant recipients. Material and methods. HRQOL was measured before and after transplantation using the SF-36® Health Survey. Clinical data [diagnosis, model of end-stage liver disease (MELD) score, post-transplant rejection and infection episodes], pre-transplant functional performance (FP), and demographics were collected. Multivariate models for the eight SF-36 scales and two summary components were developed using multiple regression. Discriminant analysis was used to test whether the score profiles differentiated among recipients with and without hepatitis C virus (HCV) infection. Results. 104 adults reported pre- and post-transplant HRQOL. Time post-transplant averaged 9±8 months (range 1–39). Scores on all SF-36 measures improved from pre- to post-transplant (p<0.001), and 7 of 10 models were significant (p<0.05). After controlling for pre-transplant HRQOL and time post-transplant, HCV infection had a negative effect on the role physical, bodily pain, and role emotional scales. History of a rejection episode had a negative effect on the bodily pain and vitality scales. MELD scores ≥18 had a positive effect on the role physical scale. Pre-transplant FP and post-transplant infection episodes did not affect post-transplant HRQOL. HCV infection had a significant effect on the SF-36 score profile (canonical correlation=0.50; p<0.001). Conclusions. Pre-transplant HCV infection...

Lateralization of Temporal Lobe Epilepsy by Imaging-Based Response-Driven Multinomial Multivariate Models

Nazem-Zadeh, Mohammad R.; Schwalb, Jason M.; Bagher-Ebadian, Hassan; Mahmoudi, Fariborz; Jafari-Khouzani, Kourosh; Elisevich, Kost V.; Soltanian-Zadeh, Hamid
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em //2014 Português
Relevância na Pesquisa
46.13%
We have developed response-driven multinomial models, based on multivariate imaging features, to lateralize the epileptogenicity in temporal lobe epilepsy (TLE) patients. To this end, volumetrics and statistical quantities of FLAIR intensity and normalized ictal–interictal SPECT intensity on left and right hippocampi were extracted from preoperative images of forty-five retrospective TLE patients with surgical outcome of Engel class I. Using multinomial logistic function regression, the parameters of various univariate and multivariate models were estimated. Among univariate response models, the response model with SPECT attributes and response model with mean FLAIR attributes achieved the lowest fit deviance (65.1±0.2 and 65.5±0.3, respectively). They resulted in the highest probability of detection (0.82) and lowest probability of false alarm (0.02) for the epileptogenic side. The multivariate response model with incorporating all volumetrics, mean and standard deviation FLAIR, and SPECT attributes achieved a significantly lower fit deviance than other response models (11.9±0.1, p < 0.001). It reached probability of detection of 1 with no false alarms. We were able to correctly lateralize the fifteen TLE patients who had undergone phase II intracranial monitoring. Therefore...

Prediction of the sensory acceptance of fruits by physical and physical-chemical parameters using multivariate models

Fonte: International Union of Food Science and Technology Publicador: International Union of Food Science and Technology
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
56.05%
Data about overall liking and physical and physical–chemical analysis for oranges, pineapples, and grapes were analyzed by Principal Component Analysis (PCA). Results showed that solid soluble variables, soluble solids content/total titratable acidity ratio, and pH contributed positively and titratable acidity contributed negatively to the overall liking grade, indicating preference for sweeter and less acidic fruit samples. Consumer acceptances were calibrated against physical and physical–chemical measurements of those fruits using Multiple Linear Regression. The models obtained were then validated and tested using the widely used methods of y-randomization and external validation. In all cases, multivariate models presented R2 values >0.7, which were higher than for the univariate models. Therefore, the models built and validated for oranges, pineapples, and grapes can be used to predict the consumer acceptance by easy and quick physical and physical–chemical measurements, ensuring that fruit commercialization takes sensory acceptance into consideration.

The accuracy of multivariate models predicting ovarian reserve and pregnancy after in vitro fertilization: a meta-analysis

Verhagen, T.; Hendriks, D.; Bancsi, L.; Mol, B.; Broekmans, F.
Fonte: Oxford University Press Publicador: Oxford University Press
Tipo: Artigo de Revista Científica
Publicado em //2008 Português
Relevância na Pesquisa
66.2%
BACKGROUND To review the accuracy of multivariate models for the prediction of ovarian reserve and pregnancy in women undergoing IVF compared with the antral follicle count (AFC) as single test. METHODS We performed a computerized MEDLINE and EMBASE search to identify articles published on multivariate models for ovarian reserve testing in patients undergoing IVF. In order to be selected, articles had to contain data on the outcome of IVF in terms of either pregnancy and/or poor response and on the prediction of these events based on a multivariate model. For the selected studies, sensitivity and specificity of the test in the prediction of poor ovarian response and non-pregnancy were calculated. Overall performance was assessed by estimating a summary receiver operating characteristic (ROC) curve, which was compared with the ROC curve for the AFC as the current best single test. RESULTS We identified 11 studies reporting on the predictive capacity of multivariate models in ovarian reserve testing. All studies reported on the prediction of poor ovarian response, whereas none reported on the occurrence of pregnancy. The sensitivity for prediction of poor ovarian response varied between 39% and 97% and the specificity between 50% and 96%. Logistic regression analysis indicated that cohort studies provided a significantly better discriminative performance than case–control studies. As cohort studies are superior to case–control studies...

Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models

CARRIERO, Andrea; KAPETANIOS, George; MARCELLINO, Massimiliano
Fonte: Instituto Universitário Europeu Publicador: Instituto Universitário Europeu
Tipo: Trabalho em Andamento Formato: application/pdf; digital
Português
Relevância na Pesquisa
56.06%
The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we propose three alternative reduced rank forecasting models and compare their predictive performance for US time series with the most promising existing alternatives, namely, factor models, large scale Bayesian VARs, and multivariate boosting. Speci.cally, we focus on classical reduced rank regression, a two-step procedure that applies, in turn, shrinkage and reduced rank restrictions, and the reduced rank Bayesian VAR of Geweke (1996). We find that using shrinkage and rank reduction in combination rather than separately improves substantially the accuracy of forecasts, both when the whole set of variables is to be forecast, and for key variables such as industrial production growth, inflation, and the federal funds rate. The robustness of this finding is confirmed by a Monte Carlo experiment based on bootstrapped data. We also provide a consistency result for the reduced rank regression valid when the dimension of the system tends to infinity, which opens the ground to use large scale reduced rank models for empirical analysis.

Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models

CARRIERO, Andrea; KAPETANIOS, George; MARCELLINO, Massimiliano
Fonte: Instituto Universitário Europeu Publicador: Instituto Universitário Europeu
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
46.05%
The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we propose three alternative reduced rank forecasting models and compare their predictive performance for US time series with the most promising existing alternatives, namely, factor models, large-scale Bayesian VARs, and multivariate boosting. Specifically, we focus on classical reduced rank regression, a two-step procedure that applies, in turn, shrinkage and reduced rank restrictions, and the reduced rank Bayesian VAR of Geweke (1996). We find that using shrinkage and rank reduction in combination rather than separately improves substantially the accuracy of forecasts, both when the whole set of variables is to be forecast and for key variables such as industrial production growth, inflation, and the federal funds rate. The robustness of this finding is confirmed by a Monte Carlo experiment based on bootstrapped data. We also provide a consistency result for the reduced rank regression valid when the dimension of the system tends to infinity, which opens the way to using large-scale reduced rank models for empirical analysis.; (Published version of EUI ECO Working Paper 2009/31.)

Comparing univariate and multivariate models to forecast portfolio value-at-risk

Santos, André A. P.; Nogales, Francisco J.; Ruiz, Esther
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: Trabalho em Andamento Formato: application/pdf
Publicado em /11/2009 Português
Relevância na Pesquisa
46.11%
This article addresses the problem of forecasting portfolio value-at-risk (VaR) with multivariate GARCH models vis-à-vis univariate models. Existing literature has tried to answer this question by analyzing only small portfolios and using a testing framework not appropriate for ranking VaR models. In this work we provide a more comprehensive look at the problem of portfolio VaR forecasting by using more appropriate statistical tests of comparative predictive ability. Moreover, we compare univariate vs. multivariate VaR models in the context of diversified portfolios containing a large number of assets and also provide evidence based on Monte Carlo experiments. We conclude that, if the sample size is moderately large, multivariate models outperform univariate counterparts on an out-of-sample basis.

Estimation of State Space Models and Stochastic Volatility

Miller Lira, Shirley
Fonte: Université de Montréal Publicador: Université de Montréal
Tipo: Thèse ou Mémoire numérique / Electronic Thesis or Dissertation
Português
Relevância na Pesquisa
46.1%
Ma thèse est composée de trois chapitres reliés à l'estimation des modèles espace-état et volatilité stochastique. Dans le première article, nous développons une procédure de lissage de l'état, avec efficacité computationnelle, dans un modèle espace-état linéaire et gaussien. Nous montrons comment exploiter la structure particulière des modèles espace-état pour tirer les états latents efficacement. Nous analysons l'efficacité computationnelle des méthodes basées sur le filtre de Kalman, l'algorithme facteur de Cholesky et notre nouvelle méthode utilisant le compte d'opérations et d'expériences de calcul. Nous montrons que pour de nombreux cas importants, notre méthode est plus efficace. Les gains sont particulièrement grands pour les cas où la dimension des variables observées est grande ou dans les cas où il faut faire des tirages répétés des états pour les mêmes valeurs de paramètres. Comme application, on considère un modèle multivarié de Poisson avec le temps des intensités variables, lequel est utilisé pour analyser le compte de données des transactions sur les marchés financières. Dans le deuxième chapitre, nous proposons une nouvelle technique pour analyser des modèles multivariés à volatilité stochastique. La méthode proposée est basée sur le tirage efficace de la volatilité de son densité conditionnelle sachant les paramètres et les données. Notre méthodologie s'applique aux modèles avec plusieurs types de dépendance dans la coupe transversale. Nous pouvons modeler des matrices de corrélation conditionnelles variant dans le temps en incorporant des facteurs dans l'équation de rendements...

Modelos multinomiais multivariados aplicados em sequências de DNA; Multivariate multinomial models applied do DNA sequences

Beatriz Castro Dias Cuyabano
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 25/02/2011 Português
Relevância na Pesquisa
45.99%
Modelos Multivariados são propostos para descrever a frequência de códons em sequências de DNA, bem como a ordem e frequência em que as bases nitrogenadas se apresentam em cada códon, considerando a dependência entre as bases dentro do códon. Modelos logísticos regressivos são utilizados com diferentes estruturas de dependência entre as posições do códon. Também, modelos baseados em uma extensão da representação de Bahadur para o caso multinomial são propostos para explicar dados multinomiais correlacionados. Uma aplicação desses modelos para o gene NADH4 do genoma mitocondrial humano é apresentada, e comparações desses modelos são feitas a partir de diferentes critérios como AIC, BIC e validação cruzada. Por fim, uma breve análise de diagnósticos é realizada para os modelos logísticos regressivo; Multivariate models are proposed to describe the codons frequencies in DNA sequences, as well as the order and frequency that nucleotide bases have in each codon, considering the dependence among the bases inside a codon. Logistic regressive models are used with different structures of dependence among the three positions in a codon. Also, models based on a multinomial extension of the Bahadur's representation are proposed to explain correlated multinomial data. An application of these models to the NADH4 gene from human mitochondrial genome is presented...

Predicting the outcome of acute stroke: prospective evaluation of five multivariate models and comparison with simple methods.

Gladman, J R; Harwood, D M; Barer, D H
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em /05/1992 Português
Relevância na Pesquisa
46.13%
Five multivariate models designed to predict the outcome of stroke were tested prospectively on 102 consecutive stroke patients admitted to a district general hospital. The results were compared with predictions made using two simple clinical variables (the conscious level on admission and the state of urinary continence at four weeks). Of the three models (developed in Belfast, Guy's Hospital and Uppsala) intended for use in the acute stages of stroke the last two were slightly more accurate in their prediction of death (75%) than was the admission conscious level alone (65%), whereas the Belfast model had an accuracy of only 50% in this situation. At a later stage, the state of urinary continence predicted good and poor outcomes with similar accuracy to that of a multivariate model from Edinburgh. A model developed in Bristol performed poorly. When tested prospectively, these multivariate models proved considerably less accurate than when they were first described. Only the Uppsala model showed any advantage over simple clinical methods. This might be of value in defining prognostic strata for clinical studies, but not in the management of individual patients. Simple clinical variables thus offer as much to clinicians as complex multivariate models.

Developing Multivariate Models For Earthquake Casualty Estimation

Tierney, Kathleen J.
Fonte: Disaster Research Center Publicador: Disaster Research Center
Tipo: Outros Formato: 184611 bytes; application/pdf
Português
Relevância na Pesquisa
45.87%
Considerable emphasis has been given in recent years to the development of methodologies for use in earthquake loss estimation (c.f., Steinbrugge, 1982; Applied Technology Council, 1985). Spangle, et al., 1987; Panel on Earthquake Loss Estimation, 1989). While the results of these efforts are impressive, and while we now know considerably more about potential earthquake losses that we did ten years ago, this knowledge is still quite uneven and incomplete (Tierney, 1990). For example, we know much more about probable losses to the building stock than about other kinds of losses, and the data base lacks regional balance.

Indicadores clínicos e pré-hospitalares de sobrevivência no trauma fechado: uma análise multivariada; Indicadores clínicos y prehospitalarios de supervivencia al trauma cerrado: un análisis multivariado; Clinical and prehospital survival indicators in blunt trauma: a multivariate analysis

Malvestio, Marisa Aparecida Amaro; Sousa, Regina Marcia Cardoso de
Fonte: Universidade de São Paulo. Escola de Enfermagem Publicador: Universidade de São Paulo. Escola de Enfermagem
Tipo: info:eu-repo/semantics/article; info:eu-repo/semantics/publishedVersion; Artigo Avaliado pelos Pares Formato: application/pdf; application/pdf
Publicado em 01/06/2010 Português
Relevância na Pesquisa
45.92%
O objetivo do estudo foi identificar os indicadores clínicos e pré-hospitalares associados à sobrevivência de vítimas de trauma fechado. Foram utilizadas a análise de sobrevivência de Kaplan Meier, e de Riscos Proporcionais de Cox, para analisar a associação de 33 variáveis ao óbito precoce e tardio, propondo modelos multivariados. Os modelos finais até 48h pós-trauma evidenciaram altos coeficientes de risco promovidos pelas lesões abdominais, Injury Severity Score >;25, procedimentos respiratórios avançados e compressões torácicas pré-hospitalares. No modelo até 7 dias, a pressão arterial sistólica na cena do acidente, se menor de 75mmHg, foi associada a maior risco de óbito e se ausente, foi associada ao mais elevado risco de óbito após 7 dias. A reposição de volume pré-hospitalar apresentou efeito protetor em todos os períodos. Os resultados sugerem que a magnitude da hipoxemia e da instabilidade hemodinâmica diante da hemorragia, influenciaram de forma significante o óbito precoce e tardio desse grupo de vítimas.; El objetivo del estudio fue identificar los indicadores clínicos y prehospitalarios asociados a la supervivencia de víctimas de trauma cerrado. Fueron utilizados el Análisis de Supervivencia de Kaplan-Meier y de Riesgos Proporcionales de Cox para examinar la asociación de 33 variables respecto de la muerte temprana y tardía...

VALOR DE MERCADO E FUNDAMENTOS CONTÁBEIS: uma avaliação a partir de modelos uni e multivariados de previsão.; MARKET VALUE AND ACCOUNTING GROUNDS: A REVIEW FROM UNIVARIATE AND MULTIVARIATE MODELS OF FORECAST.

Campos, Octávio Valente; Lamounier, Wagner Moura; Bressan, Aureliano Angel
Fonte: Universidade de São Paulo. Faculdade de Economia, Administração e Contabilidade de RP Publicador: Universidade de São Paulo. Faculdade de Economia, Administração e Contabilidade de RP
Tipo: info:eu-repo/semantics/article; info:eu-repo/semantics/publishedVersion; ; Pesquisa Empírica; ; ; ; ; ; Formato: application/pdf
Publicado em 21/04/2015 Português
Relevância na Pesquisa
46.17%
O objetivo desta pesquisa foi comparar a rentabilidade de carteiras formadas a partir dos melhores modelos de previsão univariados e multivariados, identificando a relevância da informação contábil. Tal comparação foi feita por meio do uso de previsões com os modelos ARIMA (univariados) e os modelos VAR (multivariados). Os indicadores contábeis e os retornos das ações foram utilizados como dados de entrada para a geração das previsões e consequente formação de carteiras de investimentos – a série temporal de análise inicia-se em 30/03/1994, findando-se em 30/09/2011, com dados trimestrais. Dentro de uma amostra de 20 empresas, as carteiras de investimento foram composta pelas 5 empresas com maior rentabilidade prevista, comparando-se posteriormente as rentabilidades das carteiras formadas pelos modelos univariados contra as carteiras formadas pelos modelos multivariados. Os resultados apontaram que, de forma geral, que as previsões baseadas em modelos multivariados tendem a fornecer aos investidores retornos superiores em investimentos de longo prazo (1 ano). Já os modelos univariados tendem a fornecer aos investidores retornos superiores em investimentos de custo prazo (1 trimestre). Assim, pode-se concluir que as informações contábeis em modelos de previsão apresentam maior relevância em estratégias de longo prazo. ; The objective of this research was to compare the profitability of portfolios formed from the best univariate and multivariate models of forecast...