931 resultados para success models comparison


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This study compares gridded European seasonal series of surface air temperature (SAT) and precipitation (PRE) reconstructions with a regional climate simulation over the period 1500–1990. The area is analysed separately for nine subareas that represent the majority of the climate diversity in the European sector. In their spatial structure, an overall good agreement is found between the reconstructed and simulated climate features across Europe, supporting consistency in both products. Systematic biases between both data sets can be explained by a priori known deficiencies in the simulation. Simulations and reconstructions, however, largely differ in the temporal evolution of past climate for European subregions. In particular, the simulated anomalies during the Maunder and Dalton minima show stronger response to changes in the external forcings than recorded in the reconstructions. Although this disagreement is to some extent expected given the prominent role of internal variability in the evolution of regional temperature and precipitation, a certain degree of agreement is a priori expected in variables directly affected by external forcings. In this sense, the inability of the model to reproduce a warm period similar to that recorded for the winters during the first decades of the 18th century in the reconstructions is indicative of fundamental limitations in the simulation that preclude reproducing exceptionally anomalous conditions. Despite these limitations, the simulated climate is a physically consistent data set, which can be used as a benchmark to analyse the consistency and limitations of gridded reconstructions of different variables. A comparison of the leading modes of SAT and PRE variability indicates that reconstructions are too simplistic, especially for precipitation, which is associated with the linear statistical techniques used to generate the reconstructions. The analysis of the co-variability between sea level pressure (SLP) and SAT and PRE in the simulation yields a result which resembles the canonical co-variability recorded in the observations for the 20th century. However, the same analysis for reconstructions exhibits anomalously low correlations, which points towards a lack of dynamical consistency between independent reconstructions.

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Denosumab reduced the incidence of new fractures in postmenopausal women with osteoporosis by 68% at the spine and 40% at the hip over 36 months compared with placebo in the FREEDOM study. This efficacy was supported by improvements from baseline in vertebral (18.2%) strength in axial compression and femoral (8.6%) strength in sideways fall configuration at 36 months, estimated in Newtons by an established voxel-based finite element (FE) methodology. Since FE analyses rely on the choice of meshes, material properties, and boundary conditions, the aim of this study was to independently confirm and compare the effects of denosumab on vertebral and femoral strength during the FREEDOM trial using an alternative smooth FE methodology. Unlike the previous FE study, effects on femoral strength in physiological stance configuration were also examined. QCT data for the proximal femur and two lumbar vertebrae were analyzed by smooth FE methodology at baseline, 12, 24, and 36 months for 51 treated (denosumab) and 47 control (placebo) subjects. QCT images were segmented and converted into smooth FE models to compute bone strength. L1 and L2 vertebral bodies were virtually loaded in axial compression and the proximal femora in both fall and stance configurations. Denosumab increased vertebral body strength by 10.8%, 14.0%, and 17.4% from baseline at 12, 24, and 36 months, respectively (p < 0.0001). Denosumab also increased femoral strength in the fall configuration by 4.3%, 5.1%, and 7.2% from baseline at 12, 24, and 36 months, respectively (p < 0.0001). Similar improvements were observed in the stance configuration with increases of 4.2%, 5.2%, and 5.2% from baseline (p ≤ 0.0007). Differences between the increasing strengths with denosumab and the decreasing strengths with placebo were significant starting at 12 months (vertebral and femoral fall) or 24 months (femoral stance). Using an alternative smooth FE methodology, we confirmed the significant improvements in vertebral body and proximal femur strength previously observed with denosumab. Estimated increases in strength with denosumab and decreases with placebo were highly consistent between both FE techniques.

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OBJECTIVE Telomere length is a marker of biological aging that has been linked to cardiovascular disease risk. The black South African population is witnessing a tremendous increase in the prevalence of cardiovascular disease, part of which might be explained through urbanization. We compared telomere length between black South Africans and white South Africans and examined which biological and psychosocial variables played a role in ethnic difference in telomere length. METHODS We measured leukocyte telomere length in 161 black South African teachers and 180 white South African teachers aged 23 to 66 years without a history of atherothrombotic vascular disease. Age, sex, years having lived in the area, human immunodeficiency virus (HIV) infection, hypertension, body mass index, dyslipidemia, hemoglobin A1c, C-reactive protein, smoking, physical activity, alcohol abuse, depressive symptoms, psychological distress, and work stress were considered as covariates. RESULTS Black participants had shorter (median, interquartile range) relative telomere length (0.79, 0.70-0.95) than did white participants (1.06, 0.87-1.21; p < .001), and this difference changed very little after adjusting for covariates. In fully adjusted models, age (p < .001), male sex (p = .011), and HIV positive status (p = .023) were associated with shorter telomere length. Ethnicity did not significantly interact with any covariates in determining telomere length, including psychosocial characteristics. CONCLUSIONS Black South Africans showed markedly shorter telomeres than did white South African counterparts. Age, male sex, and HIV status were associated with shorter telomere length. No interactions between ethnicity and biomedical or psychosocial factors were found. Ethnic difference in telomere length might primarily be explained by genetic factors.

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In this paper, we evaluate the impact of associational life on individual political trust in 57 Swiss municipalities. Our hierarchical regression models show that individual political trust is not only affected by individual associational membership but also by the exchange between associations and local political authorities in a community. In other words, if political authorities and associations are linked at the community level, citizens will place more trust in their local institutions. Furthermore, we find clear evidence for the rainmaker hypothesis: our results show that the positive effect of a vibrant connection between associational life and local politics on political trust is not solely confined to the associational members themselves, but rather indicate that the structure of the local civic culture fosters political trust among members and non-members at the same time. However, the internal democratic processes of associations have no effect on individuals’ trust in local political institutions.

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Recent research emphasizes the various facets of narcissism. As a consequence, newly developed questionnaires for narcissism have a large number of subscales and items. However, for the daily use in research and practice, short measures are crucial. In this study we compare different short forms of the Pathological Narcissism Questionnaire, a 54 item measure with seven subscales. In different samples (total N>2000) we applied different theoretical models to construct short forms of approximately 20 items. In particular, we compared IRT, item-total correlation, and factor loading based short forms and versions based on content validity and random selection. In all versions the original subscale structure was preserved. Results show that the short forms all have high correlations with the original version. Furthermore, correlations with criterion validation measures were comparable. We conclude that the item number can be reduced substantially without loosing information. Pros and cons of the different reduction methods are discussed.

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We present recent improvements of the modeling of the disruption of strength dominated bodies using the Smooth Particle Hydrodynamics (SPH) technique. The improvements include an updated strength model and a friction model, which are successfully tested by a comparison with laboratory experiments. In the modeling of catastrophic disruptions of asteroids, a comparison between old and new strength models shows no significant deviation in the case of targets which are initially non-porous, fully intact and have a homogeneous structure (such as the targets used in the study by Benz and Asphaug, 1999). However, for many cases (e.g. initially partly or fully damaged targets and rubble-pile structures) we find that it is crucial that friction is taken into account and the material has a pressure dependent shear strength. Our investigations of the catastrophic disruption threshold (27, as a function of target properties and target sizes up to a few 100 km show that a fully damaged target modeled without friction has a Q(D)*:, which is significantly (5-10 times) smaller than in the case where friction is included. When the effect of the energy dissipation due to compaction (pore crushing) is taken into account as well, the targets become even stronger (Q(D)*; is increased by a factor of 2-3). On the other hand, cohesion is found to have an negligible effect at large scales and is only important at scales less than or similar to 1 km. Our results show the relative effects of strength, friction and porosity on the outcome of collisions among small (less than or similar to 1000 km) bodies. These results will be used in a future study to improve existing scaling laws for the outcome of collisions (e.g. Leinhardt and Stewart, 2012). (C) 2014 Elsevier Ltd. All rights reserved.

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Using miniature thermistors with integrated data loggers, the decrease in summer lake surface water temperature (LSWT) with increasing altitude a.s.l. was investigated in 10 Swiss Alpine lakes located between 613 m a.s.l. and 2339 m a.s.l. The LSWTs exhibit essentially the same short-term structure as regional air temperature, but are about 3 to 5°C higher than the air temperature at the altitude of the lake. LSWTs decrease approximately linearly with increasing altitude at a rate slightly greater than the surface air temperature lapse rate. Diel variations in LSWT are large, implying that single water temperature measurements are un- likely to be representative of the mean. Local factors will affect LSWT more than they affect air temperature, possibly resulting in severe distortion of the empirical relationship between the two. Several implications for paleoclimate reconstruction studies result. (1) Paleolimnologically reconstructed LSWTs are likely to be higher than the air temperatures prevailing at the altitude of the lake. (2) Lakes used for paleoclimate reconstruction should be selected to minimize local effects on LSWT. (3) The calibration of organism-specific quantitative paleotemperature inference models should not be based on single water temperature measurements. (4) Consideration should be given to calibrating such models directly against air temperature rather than water temperature. (5) The primary climate effect on the aquatic biota of high-altitude lakes may be mediated by the timing of the ice cover.

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Researchers have noted that relationships created between instructors and clients in therapeutic wilderness experiences are unique (Russell, 2003; Russell & Phillips-Miller, 2001; Sklar, Anderson, & Autry, 2007; Taniguchi et al., 2009), but little research has been done to explore these relationships. The present study is an investigation of how instructors build and maintain relationships with participants, conceptualize these relationships, and define success in these tasks. Nine instructors from a wilderness program for at-risk youth participated in interviews. Data were analyzed using a line-by-line coding technique. Results of this study add to existing research on wilderness therapy and therapeutic wilderness experiences, provide models of successful instructing, and guide programs and instructors in the services they provide to their participants.

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Hierarchically clustered populations are often encountered in public health research, but the traditional methods used in analyzing this type of data are not always adequate. In the case of survival time data, more appropriate methods have only begun to surface in the last couple of decades. Such methods include multilevel statistical techniques which, although more complicated to implement than traditional methods, are more appropriate. ^ One population that is known to exhibit a hierarchical structure is that of patients who utilize the health care system of the Department of Veterans Affairs where patients are grouped not only by hospital, but also by geographic network (VISN). This project analyzes survival time data sets housed at the Houston Veterans Affairs Medical Center Research Department using two different Cox Proportional Hazards regression models, a traditional model and a multilevel model. VISNs that exhibit significantly higher or lower survival rates than the rest are identified separately for each model. ^ In this particular case, although there are differences in the results of the two models, it is not enough to warrant using the more complex multilevel technique. This is shown by the small estimates of variance associated with levels two and three in the multilevel Cox analysis. Much of the differences that are exhibited in identification of VISNs with high or low survival rates is attributable to computer hardware difficulties rather than to any significant improvements in the model. ^

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The goal of this paper is to establish if unemployment insurance policies are more generous in Europe than in the United States, and by how much. We take the examples of France and one particular American state, Ohio, and use the methodology of Pallage, Scruggs and Zimmermann (2008) to find a unique parameter value for each region that fully characterizes the generosity of the system. These two values can then be used in structural models that compare the regions, for example to explain the differences in unemployment rates.

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With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

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The relative merits of PBSCT versus BMT for children with standard and high risk hematologic malignancies remain unclear. In a retrospective single center study, we compared allogeneic peripheral blood stem cell transplantation (PBSCT) (n=30) with bone marrow transplantation (BMT) (n=110) in children with acute leukemia. We studied recipients of HLA matched sibling stem cells, and of stem cells from alternative donors (HLA mismatched and/or unrelated) and determined whether sourcing the stem cells from PB or marrow affected engraftment, incidence of acute and chronic GvHD, and disease-free survival at 1 year. Our results show a modest reduction in time to engraftment from PB stem cells and no greater risk of GvHD, but illustrate that the severity of the underlying disease is by far the greatest determinant of 1 year survival. Patients in the BMT group had a higher treatment success rate and lower costs than the recipients of the PBSCT within the standard but not the high risk disease group, where the treatment success rate and the cumulative costs were lower in the PBSCT group compared to the BMT group. Our current incremental cost-effectiveness ratio and analysis of uncertainty suggest that allogeneic transplantation of bone marrow grafts was a more cost-effective treatment option compared to peripheral blood stem cells in patients with standard risk childhood acute leukemia disease. For high risk disease our data are less prescriptive, since the differences were more limited and the range of costs much larger. Neither option demonstrated a clear advantage from a cost-effectiveness standpoint.^

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Many public health agencies and researchers are interested in comparing hospital outcomes, for example, morbidity, mortality, and hospitalization across areas and hospitals. However, since there is variation of rates in clinical trials among hospitals because of several biases, we are interested in controlling for the bias and assessing real differences in clinical practices. In this study, we compared the variations between hospitals in rates of severe Intraventricular Haemorrhage (IVH) infant using Frequentist statistical approach vs. Bayesian hierarchical model through simulation study. The template data set for simulation study was included the number of severe IVH infants of 24 intensive care units in Australian and New Zealand Neonatal Network from 1995 to 1997 in severe IVH rate in preterm babies. We evaluated the rates of severe IVH for 24 hospitals with two hierarchical models in Bayesian approach comparing their performances with the shrunken rates in Frequentist method. Gamma-Poisson (BGP) and Beta-Binomial (BBB) were introduced into Bayesian model and the shrunken estimator of Gamma-Poisson (FGP) hierarchical model using maximum likelihood method were calculated as Frequentist approach. To simulate data, the total number of infants in each hospital was kept and we analyzed the simulated data for both Bayesian and Frequentist models with two true parameters for severe IVH rate. One was the observed rate and the other was the expected severe IVH rate by adjusting for five predictors variables for the template data. The bias in the rate of severe IVH infant estimated by both models showed that Bayesian models gave less variable estimates than Frequentist model. We also discussed and compared the results from three models to examine the variation in rate of severe IVH by 20th centile rates and avoidable number of severe IVH cases. ^

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Radiation therapy has been used as an effective treatment for malignancies in pediatric patients. However, in many cases, the side effects of radiation diminish these patients’ quality of life. In order to develop strategies to minimize radiogenic complications, one must first quantitatively estimate pediatric patients’ relative risk for radiogenic late effects, which has not become feasible till recently because of the calculational complexity. The goals of this work were to calculate the dose delivered to tissues and organs in pediatric patients during contemporary photon and proton radiotherapies; to estimate the corresponding risk of radiogenic second cancer and cardiac toxicity based on the calculated doses and on dose-risk models from the literature; to test for the statistical significance of the difference between predicted risks after photon versus proton radiotherapies; and to provide a prototype of an evidence-based approach to selecting treatment modalities for pediatric patients, taking second cancer and cardiac toxicity into account. The results showed that proton therapy confers a lower predicted risk of radiogenic second cancer, and lower risks of radiogenic cardiac toxicities, compared to photon therapy. An uncertainty analysis revealed that the qualitative findings of this study are insensitive to changes in a wide variety of host and treatment related factors.

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This study demonstrated that accurate, short-term forecasts of Veterans Affairs (VA) hospital utilization can be made using the Patient Treatment File (PTF), the inpatient discharge database of the VA. Accurate, short-term forecasts of two years or less can reduce required inventory levels, improve allocation of resources, and are essential for better financial management. These are all necessary achievements in an era of cost-containment.^ Six years of non-psychiatric discharge records were extracted from the PTF and used to calculate four indicators of VA hospital utilization: average length of stay, discharge rate, multi-stay rate (a measure of readmissions) and days of care provided. National and regional levels of these indicators were described and compared for fiscal year 1984 (FY84) to FY89 inclusive.^ Using the observed levels of utilization for the 48 months between FY84 and FY87, five techniques were used to forecast monthly levels of utilization for FY88 and FY89. Forecasts were compared to the observed levels of utilization for these years. Monthly forecasts were also produced for FY90 and FY91.^ Forecasts for days of care provided were not produced. Current inpatients with very long lengths of stay contribute a substantial amount of this indicator and it cannot be accurately calculated.^ During the six year period between FY84 and FY89, average length of stay declined substantially, nationally and regionally. The discharge rate was relatively stable, while the multi-stay rate increased slightly during this period. FY90 and FY91 forecasts show a continued decline in the average length of stay, while the discharge rate is forecast to decline slightly and the multi-stay rate is forecast to increase very slightly.^ Over a 24 month ahead period, all three indicators were forecast within a 10 percent average monthly error. The 12-month ahead forecast errors were slightly lower. Average length of stay was less easily forecast, while the multi-stay rate was the easiest indicator to forecast.^ No single technique performed significantly better as determined by the Mean Absolute Percent Error, a standard measure of error. However, Autoregressive Integrated Moving Average (ARIMA) models performed well overall and are recommended for short-term forecasting of VA hospital utilization. ^