963 resultados para Generalised Linear Modeling
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Objectives: Air-pollution exposure has been associated with increased cardiovascular hospital admissions and mortality in time-series studies. We evaluated the relation between air pollutants and emergency room (ER) visits because of cardiac arrhythmia in a cardiology hospital. Methods: In a time-series study, we evaluated the association between the emergency room visits as a result of cardiac arrhythmia and daily variations in SO2, CO, NO2, O-3 and PM10, from January 1998 to August 1999. The cases of arrhythmia were modelled using generalised linear Poisson regression models, controlling for seasonality (short-term and long-term trend), and weather. Results: Interquartile range increases in CO (1.5 ppm), NO2 (49,5 mu g/m(3)) and PM10 (22.2 mu g/m(3)) on the concurrent day were associated with increases of 12.3% (95% CI: 7.6% to 17.2%), 10.4% (95% CI: 5.2% to 15.9%) and 6.7% (95% CI: 1.2% to 12.4%) in arrhythmia ER visits, respectively. PM10, CO and NO2 effects were dose-dependent and gaseous pollutants had thresholds. Only CO effect resisted estimates in models with more than one pollutant. Conclusions: Our results showed that air pollutant effects on arrhythmia are predominantly acute starting at concentrations below air quality standards, and the association with CO and NO2 suggests a relevant role for pollution caused by cars.
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We analyze the influence of time-, firm-, industry- and country-level determinants of capital structure. First, we apply hierarchical linear modeling in order to assess the relative importance of those levels. We find that time and firm levels explain 78% of firm leverage. Second, we include random intercepts and random coefficients in order to analyze the direct and indirect influences of firm/industry/country characteristics on firm leverage. We document several important indirect influences of variables at industry and country-levels on firm determinants of leverage, as well as several structural differences in the financial behavior between firms of developed and emerging countries. (C) 2010 Elsevier B.V. All rights reserved.
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With a 41-society sample of 9990 managers and professionals, we used hierarchical linear modeling to investigate the impact of both macro-level and micro-level predictors on subordinate influence ethics. While we found that both macro-level and micro-level predictors contributed to the model definition, we also found global agreement for a subordinate influence ethics hierarchy. Thus our findings provide evidence that developing a global model of subordinate ethics is possible, and should be based upon multiple criteria and multilevel variables. Journal of International Business Studies (2009) 40, 1022-1045. doi:10.1057/jibs.2008.109
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Background Many studies have suggested that adolescence is a period of particular vulnerability to neurocognitive effects associated with substance misuse. However, few large studies have measured differences in cognitive performance between chronic cannabis users who started in early adolescence (before age 15) with those who started later. Aims To examine the executive functioning of individuals who started chronic cannabis use before age 15 compared with those who started chronic cannabis use after 15 and controls. Method We evaluated the performance of 104 chronic cannabis users (49 early-onset users and 55 late-onset users) and 44 controls who undertook neuropsychological tasks, with a focus on executive functioning. Comparisons involving neuropsychological measures were performed using generalised linear model analysis of variance (ANOVA). Results The early-onset group showed significantly poorer performance compared with the controls and the late-onset group on tasks assessing sustained attention, impulse control and executive functioning. Conclusions Early-onset chronic cannabis users exhibited poorer cognitive performance than controls and late-onset users in executive functioning. Chronic cannabis use, when started before age 15, may have more deleterious effects on neurocognitive functioning.
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Objectives: The present study describes the natural history of Porphyromonas gingivalis, Actinobacillus actinomycetemcomitans and Prevotella intermedia over a 5-year period and the effect of a triclosan/copolymer dentifrice on these organisms in a normal adult population. Material and Methods: Subgingival plaque samples were collected from 504 adult volunteers. Probing pocket depths (PPD) and relative attachment levels were measured using an automated probe. Participants were matched for disease status (CPI), plaque index, age and gender, and allocated to receive either a triclosan/copolymer or placebo dentifrice. Re-examination and subgingival plaque sampling was repeated after 1, 2, 3, 4 and 5 years. P. gingivalis, A. actinomycetemcomitans and P. intermedia were detected and quantitated using an enzyme linked immunosorbent assay. Logistic regression and generalised linear modelling were used to analyse the data. Results: This 5-year longitudinal study showed considerable volatility in acquisition and loss (below the level of detection) of all three organisms in this population. Relatively few subjects had these organisms on multiple occasions. While P. gingivalis was related to loss of attachment and to PPD greater than or equal to3.5 mm, there was no relationship between A. actinomycetemcomitans or P. intermedia and disease progression over the 5 years of the study. Smokers with P. gingivalis had more PPD greater than or equal to3.5 mm than smokers without this organism. There was no significant effect of the triclosan dentifrice on P. gingivalis or A. actinomycetemcomitans . Subjects using triclosan were more likely to have P. intermedia than those not using the dentifrice; however this did not translate into these subjects having higher levels of P. intermedia and its presence was uniform showing no signs of increasing over the course of the study. Conclusion: The present 5-year longitudinal study has shown the transient nature of colonisation with P. gingivalis , A. actinomycetemcomitans and P. intermedia in a normal adult population. The use of a triclosan-containing dentifrice did not lead to an overgrowth of these organisms. The clinical effect of the dentifrice would appear to be independent of its antimicrobial properties.
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Objectives: The aim of the present study was to determine the effect of unsupervised, long-term use of a 0.3% triclosan/2% copolymer dentifrice on the progression of periodontal disease in a general adult population. Methods: Five hundred and four volunteers were enrolled in a double-blind, controlled clinical trial. Participants were matched for disease status, plaque index, age and gender. At the baseline examination, probing pocket depths and relative attachment levels were recorded and participants were assigned to either the test or control group. Re-examinations took place after 6, 12, 24, 36, 48 and 60 months. Subgingival plaque samples were collected at each examination and assayed for Porphyromonas gingivalis , Actinobacillus actinomycetemcomitans and Prevotella intermedia . A generalised linear model was used to analyse the data, with a number of covariates thought to influence the responses included as the possible confounding effects. Results: The triclosan/copolymer dentifrice had a significant effect in subjects with interproximal probing depths greater than or equal to3.5 mm, where it significantly reduced the number of sites with probing depths greater than or equal to3.5 mm at the following examination, when compared with the control group (p
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Measuring perceptions of customers can be a major problem for marketers of tourism and travel services. Much of the problem is to determine which attributes carry most weight in the purchasing decision. Older travellers weigh many travel features before making their travel decisions. This paper presents a descriptive analysis of neural network methodology and provides a research technique that assesses the weighting of different attributes and uses an unsupervised neural network model to describe a consumer-product relationship. The development of this rich class of models was inspired by the neural architecture of the human brain. These models mathematically emulate the neurophysical structure and decision making of the human brain, and, from a statistical perspective, are closely related to generalised linear models. Artificial neural networks or neural networks are, however, nonlinear and do not require the same restrictive assumptions about the relationship between the independent variables and dependent variables. Using neural networks is one way to determine what trade-offs older travellers make as they decide their travel plans. The sample of this study is from a syndicated data source of 200 valid cases from Western Australia. From senior groups, active learner, relaxed family body, careful participants and elementary vacation were identified and discussed. (C) 2003 Published by Elsevier Science Ltd.
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Dissertação de mestrado integrado em Psicologia
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Objective:Innovative moments (IMs) are moments in the therapeutic dialog that constitute exceptions toward the client's problems. These narrative markers of meaning transformation are associated with change in different models of therapy and diverse diagnoses. Our goal is to test if IMs precede symptoms change, or, on the contrary, are a mere consequence of symptomatic 15 change. Method: For this purpose, IMs and symptomatology (Outcome Questionnaire-10.2) were assessed at every session in a sample of 10 cases of narrative therapy for depression. Hierarchical linear modeling was conducted to explore whether (i) IMs in a given session predict patients' symptoms in the following session and/or (ii) symptoms in a given session predict IMs in the next session. Results: Results suggested that IMs are better predictors of symptoms than the reverse. Conclusions: These results are discussed considering the contribution of meanings and narrative processes' changes to symptomatic improvement.
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Models predicting species spatial distribution are increasingly applied to wildlife management issues, emphasising the need for reliable methods to evaluate the accuracy of their predictions. As many available datasets (e.g. museums, herbariums, atlas) do not provide reliable information about species absences, several presence-only based analyses have been developed. However, methods to evaluate the accuracy of their predictions are few and have never been validated. The aim of this paper is to compare existing and new presenceonly evaluators to usual presence/absence measures. We use a reliable, diverse, presence/absence dataset of 114 plant species to test how common presence/absence indices (Kappa, MaxKappa, AUC, adjusted D-2) compare to presenceonly measures (AVI, CVI, Boyce index) for evaluating generalised linear models (GLM). Moreover we propose a new, threshold-independent evaluator, which we call "continuous Boyce index". All indices were implemented in the B10MAPPER software. We show that the presence-only evaluators are fairly correlated (p > 0.7) to the presence/absence ones. The Boyce indices are closer to AUC than to MaxKappa and are fairly insensitive to species prevalence. In addition, the Boyce indices provide predicted-toexpected ratio curves that offer further insights into the model quality: robustness, habitat suitability resolution and deviation from randomness. This information helps reclassifying predicted maps into meaningful habitat suitability classes. The continuous Boyce index is thus both a complement to usual evaluation of presence/absence models and a reliable measure of presence-only based predictions.
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Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants
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The aims of this study were to characterise the ground-level larval habitats of the mosquito Culex quinquefasciatus, to determine the relationships between habitat characteristics and larval abundance and to examine seasonal larval-stage variations in Córdoba city. Every two weeks for two years, 15 larval habitats (natural and artificial water bodies, including shallow wells, drains, retention ponds, canals and ditches) were visited and sampled for larval mosquitoes. Data regarding the water depth, temperature and pH, permanence, the presence of aquatic vegetation and the density of collected mosquito larvae were recorded. Data on the average air temperatures and accumulated precipitation during the 15 days prior to each sampling date were also obtained. Cx. quinquefasciatus larvae were collected throughout the study period and were generally most abundant in the summer season. Generalised linear mixed models indicated the average air temperature and presence of dicotyledonous aquatic vegetation as variables that served as important predictors of larval densities. Additionally, permanent breeding sites supported high larval densities. In Córdoba city and possibly in other highly populated cities at the same latitude with the same environmental conditions, control programs should focus on permanent larval habitats with aquatic vegetation during the early spring, when the Cx. quinquefasciatus population begins to increase.
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Two hypotheses for how conditions for larval mosquitoes affect vectorial capacity make opposite predictions about the relationship of adult size and frequency of infection with vector-borne pathogens. Competition among larvae produces small adult females. The competition-susceptibility hypothesis postulates that small females are more susceptible to infection and predicts frequency of infection should decrease with size. The competition-longevity hypothesis postulates that small females have lower longevity and lower probability of becoming competent to transmit the pathogen and thus predicts frequency of infection should increase with size. We tested these hypotheses for Aedes aegypti in Rio de Janeiro, Brazil, during a dengue outbreak. In the laboratory, longevity increases with size, then decreases at the largest sizes. For field-collected females, generalised linear mixed model comparisons showed that a model with a linear increase of frequency of dengue with size produced the best Akaike’s information criterion with a correction for small sample sizes (AICc). Consensus prediction of three competing models indicated that frequency of infection increases monotonically with female size, consistent with the competition-longevity hypothesis. Site frequency of infection was not significantly related to site mean size of females. Thus, our data indicate that uncrowded, low competition conditions for larvae produce the females that are most likely to be important vectors of dengue. More generally, ecological conditions, particularly crowding and intraspecific competition among larvae, are likely to affect vector-borne pathogen transmission in nature, in this case via effects on longevity of resulting adults. Heterogeneity among individual vectors in likelihood of infection is a generally important outcome of ecological conditions impacting vectors as larvae.
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The use of observer-rated scales requires that raters be trained until they have become reliable in using the scales. However, few studies properly report how training in using a given rating scale is conducted or indeed how it should be conducted. This study examined progress in interrater reliability over 6 months of training with two observer-rated scales, the Cognitive Errors Rating Scale and the Coping Action Patterns Rating Scale. The evolution of the intraclass correlation coefficients was modeled using hierarchical linear modeling. Results showed an overall training effect as well as effects of the basic training phase and of the rater calibration phase, the latter being smaller than the former. The results are discussed in terms of implications for rater training in psychotherapy research.
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Short-term dynamic psychotherapy (STDP) has rarely been investigated with regard to its underlying mechanisms of change, even if psychoanalytic theory informs us about several potential putative mechanisms of change in patients. Change in overall defensive functioning is one. In this study, we explored the role of overall defensive functioning, by comparing it on the process level with the neighbouring concept of overall coping functioning. A total of N=32 patients, mainly presenting adjustment disorder, were included in the study. The patients underwent STDP up to 40 sessions; three sessions per psychotherapy were transcribed and analyzed by using two observer-rating scales: Defense Mechanism Rating Scales (Perry, 1990) and Coping Action Patterns (Perry, Drapeau, Dunkley, & Blake, 2005). Hierarchical linear modeling was applied to model the change over the course of therapy and relate it to outcome. Results suggest that STDP has an effect on the target variable of overall defensive functioning, which was absent for overall coping functioning. Links with outcome confirm the importance of the effect. These results are discussed from methodological and clinical viewpoints.