965 resultados para Time-dependent data
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In this article, proportional hazards and logistic models for grouped survival data were extended to incorporate time-dependent covariates. The extension was motivated by a forestry experiment designed to compare five different water stresses in Eucalyptus grandis seedlings. The response was the seedling lifetime. The data set was grouped since there were just three occasions in which the seedlings was visited by the researcher. In each of these occasions also the shoot height was measured and therefore it is a time-dependent covariate. Both extended models were used in this example, and the results were very similar.
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When estimating the effect of treatment on HIV using data from observational studies, standard methods may produce biased estimates due to the presence of time-dependent confounders. Such confounding can be present when a covariate, affected by past exposure, is both a predictor of the future exposure and the outcome. One example is the CD4 cell count, being a marker for disease progression for HIV patients, but also a marker for treatment initiation and influenced by treatment. Fitting a marginal structural model (MSM) using inverse probability weights is one way to give appropriate adjustment for this type of confounding. In this paper we study a simple and intuitive approach to estimate similar treatment effects, using observational data to mimic several randomized controlled trials. Each 'trial' is constructed based on individuals starting treatment in a certain time interval. An overall effect estimate for all such trials is found using composite likelihood inference. The method offers an alternative to the use of inverse probability of treatment weights, which is unstable in certain situations. The estimated parameter is not identical to the one of an MSM, it is conditioned on covariate values at the start of each mimicked trial. This allows the study of questions that are not that easily addressed fitting an MSM. The analysis can be performed as a stratified weighted Cox analysis on the joint data set of all the constructed trials, where each trial is one stratum. The model is applied to data from the Swiss HIV cohort study.
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Understanding how aquatic species grow is fundamental in fisheries because stock assessment often relies on growth dependent statistical models. Length-frequency-based methods become important when more applicable data for growth model estimation are either not available or very expensive. In this article, we develop a new framework for growth estimation from length-frequency data using a generalized von Bertalanffy growth model (VBGM) framework that allows for time-dependent covariates to be incorporated. A finite mixture of normal distributions is used to model the length-frequency cohorts of each month with the means constrained to follow a VBGM. The variances of the finite mixture components are constrained to be a function of mean length, reducing the number of parameters and allowing for an estimate of the variance at any length. To optimize the likelihood, we use a minorization–maximization (MM) algorithm with a Nelder–Mead sub-step. This work was motivated by the decline in catches of the blue swimmer crab (BSC) (Portunus armatus) off the east coast of Queensland, Australia. We test the method with a simulation study and then apply it to the BSC fishery data.
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Secondary neurodegeneration takes place in the surrounding tissue of spinal cord trauma and modifies substantially the prognosis, considering the small diameter of its transversal axis. We analyzed neuronal and glial responses in rat spinal cord after different degree of contusion promoted by the NYU Impactor. Rats were submitted to vertebrae laminectomy and received moderate or severe contusions. Control animals were sham operated. After 7 and 30 days post surgery, stereological analysis of Nissl staining cellular profiles showed a time progression of the lesion volume after moderate injury, but not after severe injury. The number of neurons was not altered cranial to injury. However, same degree of diminution was seen in the caudal cord 30 days after both severe and moderate injuries. Microdensitometric image analysis demonstrated a microglial reaction in the white matter 30 days after a moderate contusion and showed a widespread astroglial reaction in the white and gray matters 7 days after both severities. Astroglial activation lasted close to lesion and in areas related to Wallerian degeneration. Data showed a more protracted secondary degeneration in rat spinal cord after mild contusion, which offered an opportunity for neuroprotective approaches. Temporal and regional glial responses corroborated to diverse glial cell function in lesioned spinal cord. (C) 2007 Elsevier Ltd. All rights reserved.
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In this work, an algorithm to compute the envelope of non-destructive testing (NDT) signals is proposed. This method allows increasing the speed and reducing the memory in extensive data processing. Also, this procedure presents advantage of preserving the data information for physical modeling applications of time-dependent measurements. The algorithm is conceived to be applied for analyze data from non-destructive testing. The comparison between different envelope methods and the proposed method, applied to Magnetic Bark Signal (MBN), is studied. (C) 2010 Elsevier Ltd. All rights reserved.
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The receiver-operating characteristic (ROC) curve is the most widely used measure for evaluating the performance of a diagnostic biomarker when predicting a binary disease outcome. The ROC curve displays the true positive rate (or sensitivity) and the false positive rate (or 1-specificity) for different cut-off values used to classify an individual as healthy or diseased. In time-to-event studies, however, the disease status (e.g. death or alive) of an individual is not a fixed characteristic, and it varies along the study. In such cases, when evaluating the performance of the biomarker, several issues should be taken into account: first, the time-dependent nature of the disease status; and second, the presence of incomplete data (e.g. censored data typically present in survival studies). Accordingly, to assess the discrimination power of continuous biomarkers for time-dependent disease outcomes, time-dependent extensions of true positive rate, false positive rate, and ROC curve have been recently proposed. In this work, we present new nonparametric estimators of the cumulative/dynamic time-dependent ROC curve that allow accounting for the possible modifying effect of current or past covariate measures on the discriminatory power of the biomarker. The proposed estimators can accommodate right-censored data, as well as covariate-dependent censoring. The behavior of the estimators proposed in this study will be explored through simulations and illustrated using data from a cohort of patients who suffered from acute coronary syndrome.
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To enhance the clinical value of coronary magnetic resonance angiography (MRA), high-relaxivity contrast agents have recently been used at 3T. Here we examine a uniform bilateral shadowing artifact observed along the coronary arteries in MRA images collected using such a contrast agent. Simulations were performed to characterize this artifact, including its origin, to determine how best to mitigate this effect, and to optimize a data acquisition/injection scheme. An intraluminal contrast agent concentration model was used to simulate various acquisition strategies with two profile orders for a slow-infusion of a high-relaxivity contrast agent. Filtering effects from temporally variable weighting in k-space are prominent when a centric, radial (CR) profile order is applied during contrast infusion, resulting in decreased signal enhancement and underestimation of vessel width, while both pre- and postinfusion steady-state acquisitions result in overestimation of the vessel width. Acquisition during the brief postinfusion steady-state produces the greatest signal enhancement and minimizes k-space filtering artifacts.
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BACKGROUND & AIMS: Development of strictures is a major concern for patients with eosinophilic esophagitis (EoE). At diagnosis, EoE can present with an inflammatory phenotype (characterized by whitish exudates, furrows, and edema), a stricturing phenotype (characterized by rings and stenosis), or a combination of these. Little is known about progression of stricture formation; we evaluated stricture development over time in the absence of treatment and investigated risk factors for stricture formation. METHODS: We performed a retrospective study using the Swiss EoE Database, collecting data on 200 patients with symptomatic EoE (153 men; mean age at diagnosis, 39 ± 15 years old). Stricture severity was graded based on the degree of difficulty associated with passing of the standard adult endoscope. RESULTS: The median delay in diagnosis of EoE was 6 years (interquartile range, 2-12 years). With increasing duration of delay in diagnosis, the prevalence of fibrotic features of EoE, based on endoscopy, increased from 46.5% (diagnostic delay, 0-2 years) to 87.5% (diagnostic delay, >20 years; P = .020). Similarly, the prevalence of esophageal strictures increased with duration of diagnostic delay, from 17.2% (diagnostic delay, 0-2 years) to 70.8% (diagnostic delay, >20 years; P < .001). Diagnostic delay was the only risk factor for strictures at the time of EoE diagnosis (odds ratio = 1.08; 95% confidence interval: 1.040-1.122; P < .001). CONCLUSIONS: The prevalence of esophageal strictures correlates with the duration of untreated disease. These findings indicate the need to minimize delay in diagnosis of EoE.
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Fencamfamine (FCF) is a central stimulant that facilitates central dopaminergic transmission through inhibition of dopamine uptake and enhanced release of the transmitter. We evaluated the changes in the inhibition of uptake and the release of striatal [3H]-dopamine at 9:00 and 21:00 h, times corresponding to maximal and minimal behavioral responses to FCF, respectively. Adult male Wistar rats (200-250 g) maintained on a 12-h light/12-h dark cycle (lights on at 7:00 h) were used. In the behavioral experiments the rats (N = 8 for each group) received FCF (3.5 mg/kg, ip) or saline at 9:00 or 21:00 h. Fifteen minutes after treatment the duration of activity (sniffing, rearing and locomotion) was recorded for 120 min. The basal motor activity was higher (28.6 ± 4.2 vs 8.4 ± 3.5 s) after saline administration at 21:00 h than at 9:00 h. FCF at a single dose significantly enhanced the basal motor activity (38.3 ± 4.5 vs 8.4 ± 3.5 s) and increased the duration of exploratory activity (38.3 ± 4.5 vs 32.1 ± 4.6 s) during the light, but not the dark phase. Two other groups of rats (N = 6 for each group) were decapitated at 9:00 and 21:00 h and striata were dissected for dopamine uptake and release assays. The inhibition of uptake and release of [3H]-dopamine were higher at 9:00 than at 21:00 h, suggesting that uptake inhibition and the release properties of FCF undergo daily variation. These data suggest that the circadian time-dependent effects of FCF might be related to a higher susceptibility of dopamine presynaptic terminals to the action of FCF during the light phase which corresponds to the rats' resting period
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Contexte. Les études cas-témoins sont très fréquemment utilisées par les épidémiologistes pour évaluer l’impact de certaines expositions sur une maladie particulière. Ces expositions peuvent être représentées par plusieurs variables dépendant du temps, et de nouvelles méthodes sont nécessaires pour estimer de manière précise leurs effets. En effet, la régression logistique qui est la méthode conventionnelle pour analyser les données cas-témoins ne tient pas directement compte des changements de valeurs des covariables au cours du temps. Par opposition, les méthodes d’analyse des données de survie telles que le modèle de Cox à risques instantanés proportionnels peuvent directement incorporer des covariables dépendant du temps représentant les histoires individuelles d’exposition. Cependant, cela nécessite de manipuler les ensembles de sujets à risque avec précaution à cause du sur-échantillonnage des cas, en comparaison avec les témoins, dans les études cas-témoins. Comme montré dans une étude de simulation précédente, la définition optimale des ensembles de sujets à risque pour l’analyse des données cas-témoins reste encore à être élucidée, et à être étudiée dans le cas des variables dépendant du temps. Objectif: L’objectif général est de proposer et d’étudier de nouvelles versions du modèle de Cox pour estimer l’impact d’expositions variant dans le temps dans les études cas-témoins, et de les appliquer à des données réelles cas-témoins sur le cancer du poumon et le tabac. Méthodes. J’ai identifié de nouvelles définitions d’ensemble de sujets à risque, potentiellement optimales (le Weighted Cox model and le Simple weighted Cox model), dans lesquelles différentes pondérations ont été affectées aux cas et aux témoins, afin de refléter les proportions de cas et de non cas dans la population source. Les propriétés des estimateurs des effets d’exposition ont été étudiées par simulation. Différents aspects d’exposition ont été générés (intensité, durée, valeur cumulée d’exposition). Les données cas-témoins générées ont été ensuite analysées avec différentes versions du modèle de Cox, incluant les définitions anciennes et nouvelles des ensembles de sujets à risque, ainsi qu’avec la régression logistique conventionnelle, à des fins de comparaison. Les différents modèles de régression ont ensuite été appliqués sur des données réelles cas-témoins sur le cancer du poumon. Les estimations des effets de différentes variables de tabac, obtenues avec les différentes méthodes, ont été comparées entre elles, et comparées aux résultats des simulations. Résultats. Les résultats des simulations montrent que les estimations des nouveaux modèles de Cox pondérés proposés, surtout celles du Weighted Cox model, sont bien moins biaisées que les estimations des modèles de Cox existants qui incluent ou excluent simplement les futurs cas de chaque ensemble de sujets à risque. De plus, les estimations du Weighted Cox model étaient légèrement, mais systématiquement, moins biaisées que celles de la régression logistique. L’application aux données réelles montre de plus grandes différences entre les estimations de la régression logistique et des modèles de Cox pondérés, pour quelques variables de tabac dépendant du temps. Conclusions. Les résultats suggèrent que le nouveau modèle de Cox pondéré propose pourrait être une alternative intéressante au modèle de régression logistique, pour estimer les effets d’expositions dépendant du temps dans les études cas-témoins
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In this paper we discuss both theoretical and experimental results on the time dependence of the heat capacity of oriented Mn12 magnetic clusters when a magnetic field is applied along their easy axis. Our calculations are based on the existence of two contributions. The first one is associated with the thermal populations of the 21 different Sz levels in the two potential wells of the magnetic uniaxial anisotropy and the second one is related to the transitions between the Sz levels. We compare our theoretical predictions with experimental data on the heat capacity for different resolution times at different fields and temperatures.
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The nuclear time-dependent Hartree-Fock model formulated in three-dimensional space, based on the full standard Skyrme energy density functional complemented with the tensor force, is presented. Full self-consistency is achieved by the model. The application to the isovector giant dipole resonance is discussed in the linear limit, ranging from spherical nuclei (16O and 120Sn) to systems displaying axial or triaxial deformation (24Mg, 28Si, 178Os, 190W and 238U). Particular attention is paid to the spin-dependent terms from the central sector of the functional, recently included together with the tensor. They turn out to be capable of producing a qualitative change on the strength distribution in this channel. The effect on the deformation properties is also discussed. The quantitative effects on the linear response are small and, overall, the giant dipole energy remains unaffected. Calculations are compared to predictions from the (quasi)-particle random-phase approximation and experimental data where available, finding good agreement
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Duas classes de modelos buscam explicar o padrão de ajustamento de preço das firmas: modelos tempo-dependente e estado-dependente. O objetivo deste trabalho é levantar algumas evidencias empíricas de modo a distinguir os modelos, ou seja, identificar de que maneira as firmas realmente precificam. Para isso, escolheu-se a grande desvalorização cambial de 1999 como principal ferramenta e ambiente de análise. A hipótese fundamental é que o choque cambial impacta significativamente o custo de algumas indústrias, em alguns casos induzindo-as a alterarem seus preço após o choque. A partir de uma imensa base de micro dados formada por preços que compõem o CPI, algumas estimações importantes como a probabilidade e a magnitude média das trocas foram levantadas. A magnitude é dada por uma média simples, enquanto a probabilidade é estimada pelo método da máxima verossimilhança. Os resultados indicam um comportamento de precificação similar ao proposto por modelos estado-dependente.
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This paper proposes a test for distinguishing between time-dependent and state-dependent pricing based on whether the timing of pricing changes is affected by realized or expeted inflation. Using Brazilian data and exploring a large discrepancy between realized and expected inflation in 2002-3, we obtain a strong relation between expected inflation and duration of price spells, but little effect of inflation shocks on the frequency of price adjustment. The results thus support models with timedependent pricing, where the timing for following changes is optimally chosen whenever firms adjust prices
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)