898 resultados para Context effects (Psychology)
Resumo:
Multiple outcomes data are commonly used to characterize treatment effects in medical research, for instance, multiple symptoms to characterize potential remission of a psychiatric disorder. Often either a global, i.e. symptom-invariant, treatment effect is evaluated. Such a treatment effect may over generalize the effect across the outcomes. On the other hand individual treatment effects, varying across all outcomes, are complicated to interpret, and their estimation may lose precision relative to a global summary. An effective compromise to summarize the treatment effect may be through patterns of the treatment effects, i.e. "differentiated effects." In this paper we propose a two-category model to differentiate treatment effects into two groups. A model fitting algorithm and simulation study are presented, and several methods are developed to analyze heterogeneity presenting in the treatment effects. The method is illustrated using an analysis of schizophrenia symptom data.
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Submicroscopic changes in chromosomal DNA copy number dosage are common and have been implicated in many heritable diseases and cancers. Recent high-throughput technologies have a resolution that permits the detection of segmental changes in DNA copy number that span thousands of basepairs across the genome. Genome-wide association studies (GWAS) may simultaneously screen for copy number-phenotype and SNP-phenotype associations as part of the analytic strategy. However, genome-wide array analyses are particularly susceptible to batch effects as the logistics of preparing DNA and processing thousands of arrays often involves multiple laboratories and technicians, or changes over calendar time to the reagents and laboratory equipment. Failure to adjust for batch effects can lead to incorrect inference and requires inefficient post-hoc quality control procedures that exclude regions that are associated with batch. Our work extends previous model-based approaches for copy number estimation by explicitly modeling batch effects and using shrinkage to improve locus-specific estimates of copy number uncertainty. Key features of this approach include the use of diallelic genotype calls from experimental data to estimate batch- and locus-specific parameters of background and signal without the requirement of training data. We illustrate these ideas using a study of bipolar disease and a study of chromosome 21 trisomy. The former has batch effects that dominate much of the observed variation in quantile-normalized intensities, while the latter illustrates the robustness of our approach to datasets where as many as 25% of the samples have altered copy number. Locus-specific estimates of copy number can be plotted on the copy-number scale to investigate mosaicism and guide the choice of appropriate downstream approaches for smoothing the copy number as a function of physical position. The software is open source and implemented in the R package CRLMM available at Bioconductor (http:www.bioconductor.org).
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Objective. To examine effects of primary care physicians (PCPs) and patients on the association between charges for primary care and specialty care in a point-of-service (POS) health plan. Data Source. Claims from 1996 for 3,308 adult male POS plan members, each of whom was assigned to one of the 50 family practitioner-PCPs with the largest POS plan member-loads. Study Design. A hierarchical multivariate two-part model was fitted using a Gibbs sampler to estimate PCPs' effects on patients' annual charges for two types of services, primary care and specialty care, the associations among PCPs' effects, and within-patient associations between charges for the two services. Adjusted Clinical Groups (ACGs) were used to adjust for case-mix. Principal Findings. PCPs with higher case-mix adjusted rates of specialist use were less likely to see their patients at least once during the year (estimated correlation: –.40; 95% CI: –.71, –.008) and provided fewer services to patients that they saw (estimated correlation: –.53; 95% CI: –.77, –.21). Ten of 11 PCPs whose case-mix adjusted effects on primary care charges were significantly less than or greater than zero (p < .05) had estimated, case-mix adjusted effects on specialty care charges that were of opposite sign (but not significantly different than zero). After adjustment for ACG and PCP effects, the within-patient, estimated odds ratio for any use of primary care given any use of specialty care was .57 (95% CI: .45, .73). Conclusions. PCPs and patients contributed independently to a trade-off between utilization of primary care and specialty care. The trade-off appeared to partially offset significant differences in the amount of care provided by PCPs. These findings were possible because we employed a hierarchical multivariate model rather than separate univariate models.
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Quantifying the health effects associated with simultaneous exposure to many air pollutants is now a research priority of the US EPA. Bayesian hierarchical models (BHM) have been extensively used in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for potential confounding of other pollutants and other time-varying factors. However, when the scientific goal is to estimate the impacts of many pollutants jointly, a straightforward application of BHM is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters, which often do not have an easy interpretation. In this paper we introduce a new BHM formulation, which we call "reduced BHM", aimed at analyzing clustered data sets in the presence of a large number of random effects that are not of primary scientific interest. At the first stage of the reduced BHM, we calculate the integrated likelihood of the parameter of interest (e.g. excess number of deaths attributed to simultaneous exposure to high levels of many pollutants). At the second stage, we specify a flexible random-effect distribution directly on the parameter of interest. The reduced BHM overcomes many of the challenges in the specification and implementation of full BHM in the context of a large number of nuisance parameters. In simulation studies we show that the reduced BHM performs comparably to the full BHM in many scenarios, and even performs better in some cases. Methods are applied to estimate location-specific and overall relative risks of cardiovascular hospital admissions associated with simultaneous exposure to elevated levels of particulate matter and ozone in 51 US counties during the period 1999-2005.
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In evaluating the accuracy of diagnosis tests, it is common to apply two imperfect tests jointly or sequentially to a study population. In a recent meta-analysis of the accuracy of microsatellite instability testing (MSI) and traditional mutation analysis (MUT) in predicting germline mutations of the mismatch repair (MMR) genes, a Bayesian approach (Chen, Watson, and Parmigiani 2005) was proposed to handle missing data resulting from partial testing and the lack of a gold standard. In this paper, we demonstrate an improved estimation of the sensitivities and specificities of MSI and MUT by using a nonlinear mixed model and a Bayesian hierarchical model, both of which account for the heterogeneity across studies through study-specific random effects. The methods can be used to estimate the accuracy of two imperfect diagnostic tests in other meta-analyses when the prevalence of disease, the sensitivities and/or the specificities of diagnostic tests are heterogeneous among studies. Furthermore, simulation studies have demonstrated the importance of carefully selecting appropriate random effects on the estimation of diagnostic accuracy measurements in this scenario.
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CONTEXT: The effect of a percutaneous coronary intervention (PCI) on the long-term prognosis of patients with silent ischemia after a myocardial infarction (MI) is not known. OBJECTIVE: To determine whether PCI compared with drug therapy improves long-term outcome of asymptomatic patients with silent ischemia after an MI. DESIGN, SETTING, AND PARTICIPANTS: Randomized, unblinded, controlled trial (Swiss Interventional Study on Silent Ischemia Type II [SWISSI II]) conducted from May 2, 1991, to February 25, 1997, at 3 public hospitals in Switzerland of 201 patients with a recent MI, silent myocardial ischemia verified by stress imaging, and 1- or 2-vessel coronary artery disease. Follow-up ended on May 23, 2006. INTERVENTIONS: Percutaneous coronary intervention aimed at full revascularization (n = 96) or intensive anti-ischemic drug therapy (n = 105). All patients received 100 mg/d of aspirin and a statin. MAIN OUTCOME MEASURES: Survival free of major adverse cardiac events defined as cardiac death, nonfatal MI, and/or symptom-driven revascularization. Secondary measures included exercise-induced ischemia and resting left ventricular ejection fraction during follow-up. RESULTS: During a mean (SD) follow-up of 10.2 (2.6) years, 27 major adverse cardiac events occurred in the PCI group and 67 events occurred in the anti-ischemic drug therapy group (adjusted hazard ratio, 0.33; 95% confidence interval, 0.20-0.55; P<.001), which corresponds to an absolute event reduction of 6.3% per year (95% confidence interval, 3.7%-8.9%; P<.001). Patients in the PCI group had lower rates of ischemia (11.6% vs 28.9% in patients in the drug therapy group at final follow-up; P = .03) despite fewer drugs. Left ventricular ejection fraction remained preserved in PCI patients (mean [SD] of 53.9% [9.9%] at baseline to 55.6% [8.1%] at final follow-up) and decreased significantly (P<.001) in drug therapy patients (mean [SD] of 59.7% [11.8%] at baseline to 48.8% [7.9%] at final follow-up). CONCLUSION: Among patients with recent MI, silent myocardial ischemia verified by stress imaging, and 1- or 2-vessel coronary artery disease, PCI compared with anti-ischemic drug therapy reduced the long-term risk of major cardiac events. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00387231.
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The longitudinal dimension of schizophrenia and related severe mental illness is a key component of theoretical models of recovery. However, empirical longitudinal investigations have been underrepresented in the psychopathology of schizophrenia. Similarly, traditional approaches to longitudinal analysis of psychopathological data have had serious limitations. The utilization of modern longitudinal methods is necessary to capture the complexity of biopsychosocial models of treatment and recovery in schizophrenia. The present paper summarizes empirical data from traditional longitudinal research investigating recovery in symptoms, neurocognition, and social functioning. Studies conducted under treatment as usual conditions are compared to psychosocial intervention studies and potential treatment mechanisms of psychosocial interventions are discussed. Investigations of rehabilitation for schizophrenia using the longitudinal analytic strategies of growth curve and time series analysis are demonstrated. The respective advantages and disadvantages of these modern methods are highlighted. Their potential use for future research of treatment effects and recovery in schizophrenia is also discussed.
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Anthropogenic activities continue to drive atmospheric CO2 and O3 concentrations to levels higher than during the pre-industrial era. Accumulating evidence indicates that both elevated CO2 and elevated O3 could modify the quantity and biochemistry of woody plant biomass. Anatomical properties of woody plants are largely influenced by the activity of the cambium and the growth characteristics of wood cells, which are in turn influenced by a range of environmental factors. Hence, alterations in the concentrations of atmospheric CO2 and / or O3 could also impact wood anatomical properties. Many fungi derive their metabolic resources for growth from plant litter, including woody tissue, and therefore modifications in the quantity, biochemistry and anatomical properties of woody plants in response to elevated CO2 and / or O3 could impact the community of wood-decaying fungi and rates of wood decomposition. Consequently carbon and nutrient cycling and productivity of terrestrial ecosystem could also be impacted. Alterations in wood structure and biochemistry of woody plants could also impact wood density and subsequently impact wood quality. This dissertation examined the long term effects of elevated CO2 and / or O3 on wood anatomical properties, wood density, wood-decaying fungi and wood decomposition of northern hardwood tree species at the Aspen Free-Air CO2 and O3 Enrichment (Aspen FACE) project, near Rhinelander, WI, USA. Anatomical properties of wood varied significantly with species and aspen genotypes and radial position within the stem. Elevated CO2 did not have significant effects on wood anatomical properties in trembling aspen, paper birch or sugar maple, except for marginally increasing (P < 0.1) the number of vessels per square millimeter. Elevated O3 marginally or significantly altered vessel lumen diameter, cell wall area and vessel lumen area proportions depending on species and radial position. In line with the modifications in the anatomical properties, elevated CO2 and O3, alone, significantly modified wood density but effects were species and / or genotype specific. However, the effects of elevated CO2 and O3, alone, on wood anatomical properties and density were ameliorated when in combination. Wood species had a much greater impact on the wood-decaying fungal community and initial wood decomposition rate than did growth or decomposition of wood in elevated CO2 and / or O3. Polyporales, Agaricales, and Russulales were the dominant orders of fungi isolated. Based on the current results, future higher levels of CO2 and O3 may have moderate effects on wood quality of northern hardwoods, but for utilization purposes these may not be considered significant. However, wood-decaying fungal community composition and decomposition of northern hardwoods may be altered via shifts in species and / or genotype composition under future higher levels of CO2 and O3.
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The relationship between obesity and heart rate variability (HRV) has been studied in adults and adolescents, but is not determined in young pediatrics. The purpose of this study was to assess autonomic activity using HRV in a pediatric population. We hypothesized that obese children would have reduced parasympathetic and increased sympathetic activity compared to age-matched subjects. 42 pediatric subjects (ages 3-5) were classified into 3 groups based on body mass index-for-age; normal, overweight and obese. HRV and respiratory rate were recorded during 3 minute baseline, 2 minute isometric handgrip and 3 minute recovery. HRV was analyzed in the time domain [heart rate (HR), RR interval (RRI) and RRI standard deviation (RRISD)] and frequency domain [low frequency (LF), high frequency (HF) and LF/HF ratio] using repeated measures ANOVA. Spearman’s correlations were used to examine the relations between BMI and HRV at rest. Significant condition effects were found between baseline, exercise and recovery, but these responses were not significantly different between the normal, overweight and obese children. BMI was negatively correlated with LF/HF, while BMI was positively correlated with RRISD, LF, HF and nHF. Our data demonstrate that higher BMI in the pediatric population is correlated with higher parasympathetic and lower sympathetic activity. These findings are contrary to HRV responses observed in adults and adolescents, suggesting complex relationships between age, obesity and autonomic control of the heart. The data supports the concept of an age reliance of HRV and a novel relationship between adiposity and body mass index in 3-5 year olds.
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Onondaga Lake has received the municipal effluent and industrial waste from the city of Syracuse for more than a century. Historically, 75 metric tons of mercury were discharged to the lake by chlor-alkali facilities. These legacy deposits of mercury now exist primarily in the lake sediments. Under anoxic conditions, methylmercury is produced in the sediments and can be released to the overlying water. Natural sedimentation processes are continuously burying the mercury deeper into the sediments. Eventually, the mercury will be buried to a depth where it no longer has an impact on the overlying water. In the interim, electron acceptor amendment systems can be installed to retard these chemical releases while the lake naturally recovers. Electron acceptor amendment systems are designed to meet the sediment oxygen demand in the sediment and maintain manageable hypolimnion oxygen concentrations. Historically, designs of these systems have been under designed resulting in failure. This stems from a mischaracterization of the sediment oxygen demand. Turbulence at the sediment water interface has been shown to impact sediment oxygen demand. The turbulence introduced by the electron amendment system can thus increase the sediment oxygen demand, resulting in system failure if turbulence is not factored into the design. Sediment cores were gathered and operated to steady state under several well characterized turbulence conditions. The relationship between sediment oxygen/nitrate demand and turbulence was then quantified and plotted. A maximum demand was exhibited at or above a fluid velocity of 2.0 mm•s-1. Below this velocity, demand decreased rapidly with fluid velocity as zero velocity was approached. Similar relationships were displayed by both oxygen and nitrate cores.
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The Modeling method of teaching has demonstrated well--‐documented success in the improvement of student learning. The teacher/researcher in this study was introduced to Modeling through the use of a technique called White Boarding. Without formal training, the researcher began using the White Boarding technique for a limited number of laboratory experiences with his high school physics classes. The question that arose and was investigated in this study is “What specific aspects of the White Boarding process support student understanding?” For the purposes of this study, the White Boarding process was broken down into three aspects – the Analysis of data through the use of Logger Pro software, the Preparation of White Boards, and the Presentations each group gave about their specific lab data. The lab used in this study, an Acceleration of Gravity Lab, was chosen because of the documented difficulties students experience in the graphing of motion. In the lab, students filmed a given motion, utilized Logger Pro software to analyze the motion, prepared a White Board that described the motion with position--‐time and velocity--‐time graphs, and then presented their findings to the rest of the class. The Presentation included a class discussion with minimal contribution from the teacher. The three different aspects of the White Boarding experience – Analysis, Preparation, and Presentation – were compared through the use of student learning logs, video analysis of the Presentations, and follow--‐up interviews with participants. The information and observations gathered were used to determine the level of understanding of each participant during each phase of the lab. The researcher then looked for improvement in the level of student understanding, the number of “aha” moments students had, and the students’ perceptions about which phase was most important to their learning. The results suggest that while all three phases of the White Boarding experience play a part in the learning process for students, the Presentations provided the most significant changes. The implications for instruction are discussed.
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Internal combustion engines are, and will continue to be, a primary mode of power generation for ground transportation. Challenges exist in meeting fuel consumption regulations and emission standards while upholding performance, as fuel prices rise, and resource depletion and environmental impacts are of increasing concern. Diesel engines are advantageous due to their inherent efficiency advantage over spark ignition engines; however, their NOx and soot emissions can be difficult to control and reduce due to an inherent tradeoff. Diesel combustion is spray and mixing controlled providing an intrinsic link between spray and emissions, motivating detailed, fundamental studies on spray, vaporization, mixing, and combustion characteristics under engine relevant conditions. An optical combustion vessel facility has been developed at Michigan Technological University for these studies, with detailed tests and analysis being conducted. In this combustion vessel facility a preburn procedure for thermodynamic state generation is used, and validated using chemical kinetics modeling both for the MTU vessel, and institutions comprising the Engine Combustion Network international collaborative research initiative. It is shown that minor species produced are representative of modern diesel engines running exhaust gas recirculation and do not impact the autoignition of n-heptane. Diesel spray testing of a high-pressure (2000 bar) multi-hole injector is undertaken including non-vaporizing, vaporizing, and combusting tests, with sprays characterized using Mie back scatter imaging diagnostics. Liquid phase spray parameter trends agree with literature. Fluctuations in liquid length about a quasi-steady value are quantified, along with plume to plume variations. Hypotheses are developed for their causes including fuel pressure fluctuations, nozzle cavitation, internal injector flow and geometry, chamber temperature gradients, and turbulence. These are explored using a mixing limited vaporization model with an equation of state approach for thermopyhysical properties. This model is also applied to single and multi-component surrogates. Results include the development of the combustion research facility and validated thermodynamic state generation procedure. The developed equation of state approach provides application for improving surrogate fuels, both single and multi-component, in terms of diesel spray liquid length, with knowledge of only critical fuel properties. Experimental studies are coupled with modeling incorporating improved thermodynamic non-ideal gas and fuel
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Global climate change might significantly impact future ecosystems. The purpose of this thesis was to investigate potential changes in woody plant fine root respiration in response to a changing climate. In a sugar maple dominated northern hardwood forest, the soil was experimentally warmed (+4 °C) to determine if the tree roots could metabolically acclimate to warmer soil conditions. After one and a half years of soil warming, there was an indication of slight acclimation in the fine roots of sugar maple, helping the ecosystem avoid excessive C loss to the atmosphere. In a poor fen northern peatland in northern Michigan, the impacts of water level changes on woody plant fine root respiration were investigated. In areas of increased and also decreased water levels, there were increases in the CO2 efflux from ecosystem fine root respiration. These studies show the importance of investigating further the impacts climate change may have on C balance in northern ecosystems.
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Water-saturated debris flows are among some of the most destructive mass movements. Their complex nature presents a challenge for quantitative description and modeling. In order to improve understanding of the dynamics of these flows, it is important to seek a simplified dynamic system underlying their behavior. Models currently in use to describe the motion of debris flows employ depth-averaged equations of motion, typically assuming negligible effects from vertical acceleration. However, in many cases debris flows experience significant vertical acceleration as they move across irregular surfaces, and it has been proposed that friction associated with vertical forces and liquefaction merit inclusion in any comprehensive mechanical model. The intent of this work is to determine the effect of vertical acceleration through a series of laboratory experiments designed to simulate debris flows, testing a recent model for debris flows experimentally. In the experiments, a mass of water-saturated sediment is released suddenly from a holding container, and parameters including rate of collapse, pore-fluid pressure, and bed load are monitored. Experiments are simplified to axial geometry so that variables act solely in the vertical dimension. Steady state equations to infer motion of the moving sediment mass are not sufficient to model accurately the independent solid and fluid constituents in these experiments. The model developed in this work more accurately predicts the bed-normal stress of a saturated sediment mass in motion and illustrates the importance of acceleration and deceleration.