977 resultados para Individual Variability
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This paper replicates the analysis of Scottish HEIs in Hermannsson et al (2010a) to identify the impact of London-based HEIs on the English economy in order to provide a self-contained analysis that is readily accessible by those whose primary concern is with the regional impacts of London HEIs. When we treat each of the 38 London-based Higher Education Institutions (HEIs) that existed in England in 2006 as separate sectors in conventional input-output analysis, their expenditure impacts per unit of final demand appear rather homogenous (though less so than HEIs in Wales and Scotland), with the apparent heterogeneity of their overall impacts being primarily driven by scale. However, a disaggregation of their income by source reveals considerable variation in their dependence upon general public funding and their ability to draw in income/funding from external sources. Acknowledging the possible alternative uses of the public funding and deriving balanced expenditure multipliers reveals large differences in the net-expenditure impact of London HEIs upon the English economy, with the source of variation being the origin of income. Applying a novel treatment of student expenditure impacts, identifying the amount of exogenous spending per student, modifies the heterogeneity of the overall expenditure impacts. On balance this suggests that the impacts of impending budget cut-backs will be quite different by institution depending on their sensitivity to public funding. However, predicting the outcome of budget cutbacks at the margin is problematic for reasons that we identify.
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This paper replicates the analysis of Scottish HEIs in Hermannsson et al (2010a) for the case of Northern Ireland in order to provide a self-contained analysis that is readily accessible by those whose primary concern is with the regional impacts of Northern-Irish HEIs. When we treat each of the four Higher Education Institutions (HEIs) that existed in Northern Ireland in 2006 as separate sectors in conventional input-output analysis, their expenditure impacts per unit of final demand appear rather homogenous, with the apparent heterogeneity of their overall impacts being primarily driven by scale. However, a disaggregation of their income by source reveals considerable variation in their dependence upon funding from the devolved Assembly and their ability to draw in income/funding from external sources. Acknowledging the binding budget constraint of the Northern Ireland Assembly and deriving balanced expenditure multipliers reveals large differences in the netexpenditure impact of HEIs upon the Northern Irish economy, with the source of variation being the origin of income. Applying a novel treatment of student expenditure impacts, identifying the amount of exogenous spending per student, modifies the heterogeneity of the overall expenditure impacts. On balance this suggests that the impacts of impending budget cut-backs will be quite different by institution depending on their sensitivity to public funding. However, predicting the outcome of budget cutbacks at the margin is problematic for reasons that we identify.
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A social choice function is group strategy-proof on a domain if no group of agents can manipulate its final outcome to their own benefit by declaring false preferences on that domain. Group strategy-proofness is a very attractive requirement of incentive compatibility. But in many cases it is hard or impossible to find nontrivial social choice functions satisfying even the weakest condition of individual strategy-proofness. However, there are a number of economically significant domains where interesting rules satisfying individual strategy-proofness can be defined, and for some of them, all these rules turn out to also satisfy the stronger requirement of group strategy-proofness. This is the case, for example, when preferences are single-peaked or single-dipped. In other cases, this equivalence does not hold. We provide sufficient conditions defining domains of preferences guaranteeing that individual and group strategy-proofness are equivalent for all rules defined on the
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BACKGROUND: Recommended oral voriconazole (VRC) doses are lower than intravenous doses. Because plasma concentrations impact efficacy and safety of therapy, optimizing individual drug exposure may improve these outcomes. METHODS: A population pharmacokinetic analysis (NONMEM) was performed on 505 plasma concentration measurements involving 55 patients with invasive mycoses who received recommended VRC doses. RESULTS: A 1-compartment model with first-order absorption and elimination best fitted the data. VRC clearance was 5.2 L/h, the volume of distribution was 92 L, the absorption rate constant was 1.1 hour(-1), and oral bioavailability was 0.63. Severe cholestasis decreased VRC elimination by 52%. A large interpatient variability was observed on clearance (coefficient of variation [CV], 40%) and bioavailability (CV 84%), and an interoccasion variability was observed on bioavailability (CV, 93%). Lack of response to therapy occurred in 12 of 55 patients (22%), and grade 3 neurotoxicity occurred in 5 of 55 patients (9%). A logistic multivariate regression analysis revealed an independent association between VRC trough concentrations and probability of response or neurotoxicity by identifying a therapeutic range of 1.5 mg/L (>85% probability of response) to 4.5 mg/L (<15% probability of neurotoxicity). Population-based simulations with the recommended 200 mg oral or 300 mg intravenous twice-daily regimens predicted probabilities of 49% and 87%, respectively, for achievement of 1.5 mg/L and of 8% and 37%, respectively, for achievement of 4.5 mg/L. With 300-400 mg twice-daily oral doses and 200-300 mg twice-daily intravenous doses, the predicted probabilities of achieving the lower target concentration were 68%-78% for the oral regimen and 70%-87% for the intravenous regimen, and the predicted probabilities of achieving the upper target concentration were 19%-29% for the oral regimen and 18%-37% for the intravenous regimen. CONCLUSIONS: Higher oral than intravenous VRC doses, followed by individualized adjustments based on measured plasma concentrations, improve achievement of the therapeutic target that maximizes the probability of therapeutic response and minimizes the probability of neurotoxicity. These findings challenge dose recommendations for VRC.
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The Conservative Party emerged from the 2010 United Kingdom General Election as the largest single party, but their support was not geographically uniform. In this paper, we estimate a hierarchical Bayesian spatial probit model that tests for the presence of regional voting effects. This model allows for the estimation of individual region-specic effects on the probability of Conservative Party success, incorporating information on the spatial relationships between the regions of the mainland United Kingdom. After controlling for a range of important covariates, we find that these spatial relationships are significant and that our individual region-specic effects estimates provide additional evidence of North-South variations in Conservative Party support.
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INTRODUCTION: Therapeutic hypothermia (TH) is often used to treat out-of-hospital cardiac arrest (OHCA) patients who also often simultaneously receive insulin for stress-induced hyperglycaemia. However, the impact of TH on systemic metabolism and insulin resistance in critical illness is unknown. This study analyses the impact of TH on metabolism, including the evolution of insulin sensitivity (SI) and its variability, in patients with coma after OHCA. METHODS: This study uses a clinically validated, model-based measure of SI. Insulin sensitivity was identified hourly using retrospective data from 200 post-cardiac arrest patients (8,522 hours) treated with TH, shortly after admission to the intensive care unit (ICU). Blood glucose and body temperature readings were taken every one to two hours. Data were divided into three periods: 1) cool (T <35°C); 2) an idle period of two hours as normothermia was re-established; and 3) warm (T >37°C). A maximum of 24 hours each for the cool and warm periods was considered. The impact of each condition on SI is analysed per cohort and per patient for both level and hour-to-hour variability, between periods and in six-hour blocks. RESULTS: Cohort and per-patient median SI levels increase consistently by 35% to 70% and 26% to 59% (P <0.001) respectively from cool to warm. Conversely, cohort and per-patient SI variability decreased by 11.1% to 33.6% (P <0.001) for the first 12 hours of treatment. However, SI variability increases between the 18th and 30th hours over the cool to warm transition, before continuing to decrease afterward. CONCLUSIONS: OCHA patients treated with TH have significantly lower and more variable SI during the cool period, compared to the later warm period. As treatment continues, SI level rises, and variability decreases consistently except for a large, significant increase during the cool to warm transition. These results demonstrate increased resistance to insulin during mild induced hypothermia. Our study might have important implications for glycaemic control during targeted temperature management.
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Biological features and social preferences have been studied separately as factors influencing human strategic behaviour. We run two studies in order to explore the interplay between these two sets of factors. In the first study, we investigate to what extent social preferences may have some biological underpinnings. We use simple one-shot distribution experiments to attribute subjects one out of four types of social preferences: Self-interested (SI), Competitive (C), Inequality averse (IA) and Efficiency-seeking (ES). We then investigate whether these four groups display differences in their levels of facial Fluctuating Asymmetry (FA) and in proxies for exposure to testosterone during phoetal development and puberty. We observe that development-related biological features and social preferences are relatively independent. In the second study, we compare the relative weight of these two set of factors by studying how they affect subjects’ behaviour in the Ultimatum Game (UG). We find differences in offers made and rejection rates across the four social preference groups. The effect of social preferences is stronger than the effect of biological features even though the latter is significant. We also report a novel link between facial masculinity (a proxy for exposure to testosterone during puberty) and rejection rates in the UG. Our results suggest that biological features influence behaviour both directly and through their relation with the type of social preferences that individuals hold.
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This paper discusses how to identify individual-specific causal effects of an ordered discrete endogenous variable. The counterfactual heterogeneous causal information is recovered by identifying the partial differences of a structural relation. The proposed refutable nonparametric local restrictions exploit the fact that the pattern of endogeneity may vary across the level of the unobserved variable. The restrictions adopted in this paper impose a sense of order to an unordered binary endogeneous variable. This allows for a uni.ed structural approach to studying various treatment effects when self-selection on unobservables is present. The usefulness of the identi.cation results is illustrated using the data on the Vietnam-era veterans. The empirical findings reveal that when other observable characteristics are identical, military service had positive impacts for individuals with low (unobservable) earnings potential, while it had negative impacts for those with high earnings potential. This heterogeneity would not be detected by average effects which would underestimate the actual effects because different signs would be cancelled out. This partial identification result can be used to test homogeneity in response. When homogeneity is rejected, many parameters based on averages may deliver misleading information.
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I develop a model of endogenous bounded rationality due to search costs, arising implicitly from the problems complexity. The decision maker is not required to know the entire structure of the problem when making choices but can think ahead, through costly search, to reveal more of it. However, the costs of search are not assumed exogenously; they are inferred from revealed preferences through her choices. Thus, bounded rationality and its extent emerge endogenously: as problems become simpler or as the benefits of deeper search become larger relative to its costs, the choices more closely resemble those of a rational agent. For a fixed decision problem, the costs of search will vary across agents. For a given decision maker, they will vary across problems. The model explains, therefore, why the disparity, between observed choices and those prescribed under rationality, varies across agents and problems. It also suggests, under reasonable assumptions, an identifying prediction: a relation between the benefits of deeper search and the depth of the search. As long as calibration of the search costs is possible, this can be tested on any agent-problem pair. My approach provides a common framework for depicting the underlying limitations that force departures from rationality in different and unrelated decision-making situations. Specifically, I show that it is consistent with violations of timing independence in temporal framing problems, dynamic inconsistency and diversification bias in sequential versus simultaneous choice problems, and with plausible but contrasting risk attitudes across small- and large-stakes gambles.
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In this analysis, we examine the relationship between an individual's decision to volunteer and the average level of volunteering in the community where the individual resides. Our theoretical model is based on a coordination game , in which volunteering by others is informative regarding the benefit from volunteering. We demonstrate that the interaction between this information and one's private information makes it more likely that he or she will volunteer, given a higher level of contributions by his or her peers. We complement this theoretical work with an empirical analysis using Census 2000 Summary File 3 and Current Population Survey (CPS) 2004-2007 September supplement file data. We control for various individual and community characteristics, and employ robustness checks to verify the results of the baseline analysis. We additionally use an innovative instrumental variables strategy to account for reflection bias and endogeneity caused by selective sorting by individuals into neighborhoods, which allows us to argue for a causal interpretation. The empirical results in the baseline, as well as all robustness analyses, verify the main result of our theoretical model, and we employ a more general structure to further strengthen our results.
Resumo:
In this analysis, we examine the relationship between an individual’s decision to volunteer and the average level of volunteering in the community where the individual resides. Our theoretical model is based on a coordination game , in which volunteering by others is informative regarding the benefit from volunteering. We demonstrate that the interaction between this information and one’s private information makes it more likely that he or she will volunteer, given a higher level of contributions by his or her peers. We complement this theoretical work with an empirical analysis using Census 2000 Summary File 3 and Current Population Survey (CPS) 2004-2007 September supplement file data. We control for various individual and community characteristics, and employ robustness checks to verify the results of the baseline analysis. We additionally use an innovative instrumental variables strategy to account for reflection bias and endogeneity caused by selective sorting by individuals into neighbourhoods, which allows us to argue for a causal interpretation. The empirical results in the baseline, as well as all robustness analyses, verify the main result of our theoretical model, and we employ a more general structure to further strengthen our results.
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Purpose: Revolutionary endovascular treatments are on the verge of being available for management of ascending aortic diseases. Morphometric measurements of the ascending aorta have already been done with ECG-gated MDCT to help such therapeutic development. However the reliability of these measurements remains unknown. The objective of this work was to compare the intraobserver and interobserver variability of CAD (computer aided diagnosis) versus manual measurements in the ascending aorta. Methods and materials: Twenty-six consecutive patients referred for ECG-gated CT thoracic angiography (64-row CT scanner) were evaluated. Measurements of the maximum and minimum ascending aorta diameters at mid-distance between the brachiocephalic artery and the aortic valve were obtained automatically with a commercially available CAD and manually by two observers separately. Both observers repeated the measurements during a different session at least one month after the first measurements. Intraclass coefficients as well the Bland and Altman method were used for comparison between measurements. Two-paired t-test was used to determine the significance of intraobserver and interobserver differences (alpha = 0.05). Results: There is a significant difference between CAD and manual measurements in the maximum diameter (p = 0.004) for the first observer, whereas the difference was significant for minimum diameter between the second observer and the CAD (p <0.001). Interobserver variability showed a weak agreement when measurements were done manually. Intraobserver variability was lower with the CAD compared to the manual measurements (limits of variability: from -0.7 to 0.9 mm for the former and from -1.2 to 1.3 mm for the latter). Conclusion: In order to improve reproductibility of measurements whenever needed, pre- and post-therapeutic management of the ascending aorta may benefit from follow-up done by a unique observer with the help of CAD.
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T-cell vaccination may prevent or treat cancer and infectious diseases, but further progress is required to increase clinical efficacy. Step-by-step improvements of T-cell vaccination in phase I/II clinical studies combined with very detailed analysis of T-cell responses at the single cell level are the strategy of choice for the identification of the most promising vaccine candidates for testing in subsequent large-scale phase III clinical trials. Major aims are to fully identify the most efficient T-cells in anticancer therapy, to characterize their TCRs, and to pinpoint the mechanisms of T-cell recruitment and function in well-defined clinical situations. Here we discuss novel strategies for the assessment of human T-cell responses, revealing in part unprecedented insight into T-cell biology and novel structural principles that govern TCR-pMHC recognition. Together, the described approaches advance our knowledge of T-cell mediated-protection from human diseases.