960 resultados para Binary hypothesis testing


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Introducción: El objetivo principal de la selección del donante es disminuir la posibilidad de transmisión de enfermedades infecciosas o neoplásicas en el receptor. De forma cruda se calcula que aproximadamente el 50% de los potenciales donantes son contraindicados, la mayoría por infección. La alta demanda de órganos obliga a revalorar las contraindicaciones que hasta hace poco eran absolutas, el reto es diferenciar el SIRS del donante por Muerte Encefálica con el SIRS por infecciones. Método: Estudio de cohorte retrospectivo; que busca evaluar la respuesta inflamatoria sistémica (SIRS) como predictor de infección en pacientes con trasplante renal en el primer mes pos trasplante. Resultados: El contraste de hipótesis proporciono una significancia bilateral (P= 0,071). La pruebas de hipótesis aceptaron la hipótesis nula (P= 0,071), que no existe asociación entre la presencia de SIRS en el donante con la incidencia de infección en el primer mes del pos trasplante renal. La estimación del riesgo de no reingreso por infección al primer mes pos trasplante renal es de 0.881 veces para los donantes con SIRS (IC 0.757 – 1.025). Conclusión: A pesar de no encontrar significancia estadística: el SIRS en el donante no se asocia con un aumento en la incidencia de infección en el primer mes postrasplante. Para encontrar la significancia se propone un estudio con un tamaño de muestra mayor.

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The biggest challenge in conservation biology is breaking down the gap between research and practical management. A major obstacle is the fact that many researchers are unwilling to tackle projects likely to produce sparse or messy data because the results would be difficult to publish in refereed journals. The obvious solution to sparse data is to build up results from multiple studies. Consequently, we suggest that there needs to be greater emphasis in conservation biology on publishing papers that can be built on by subsequent research rather than on papers that produce clear results individually. This building approach requires: (1) a stronger theoretical framework, in which researchers attempt to anticipate models that will be relevant in future studies and incorporate expected differences among studies into those models; (2) use of modern methods for model selection and multi-model inference, and publication of parameter estimates under a range of plausible models; (3) explicit incorporation of prior information into each case study; and (4) planning management treatments in an adaptive framework that considers treatments applied in other studies. We encourage journals to publish papers that promote this building approach rather than expecting papers to conform to traditional standards of rigor as stand-alone papers, and believe that this shift in publishing philosophy would better encourage researchers to tackle the most urgent conservation problems.

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The evolutionary history of gains and losses of vegetative reproductive propagules (soredia) in Porpidia s.l., a group of lichen-forming ascomycetes, was clarified using Bayesian Markov chain Monte Carlo (MCMC) approaches to monophyly tests and a combined MCMC and maximum likelihood approach to ancestral character state reconstructions. The MCMC framework provided confidence estimates for the reconstructions of relationships and ancestral character states, which formed the basis for tests of evolutionary hypotheses. Monophyly tests rejected all hypotheses that predicted any clustering of reproductive modes in extant taxa. In addition, a nearest-neighbor statistic could not reject the hypothesis that the vegetative reproductive mode is randomly distributed throughout the group. These results show that transitions between presence and absence of the vegetative reproductive mode within Porpidia s.l. occurred several times and independently of each other. Likelihood reconstructions of ancestral character states at selected nodes suggest that - contrary to previous thought - the ancestor to Porpidia s.l. already possessed the vegetative reproductive mode. Furthermore, transition rates are reconstructed asymmetrically with the vegetative reproductive mode being gained at a much lower rate than it is lost. A cautious note has to be added, because a simulation study showed that the ancestral character state reconstructions were highly dependent on taxon sampling. However, our central conclusions, particularly the higher rate of change from vegetative reproductive mode present to absent than vice versa within Porpidia s.l., were found to be broadly independent of taxon sampling. [Ancestral character state reconstructions; Ascomycota, Bayesian inference; hypothesis testing; likelihood; MCMC; Porpidia; reproductive systems]

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Event-related functional magnetic resonance imaging (efMRI) has emerged as a powerful technique for detecting brains' responses to presented stimuli. A primary goal in efMRI data analysis is to estimate the Hemodynamic Response Function (HRF) and to locate activated regions in human brains when specific tasks are performed. This paper develops new methodologies that are important improvements not only to parametric but also to nonparametric estimation and hypothesis testing of the HRF. First, an effective and computationally fast scheme for estimating the error covariance matrix for efMRI is proposed. Second, methodologies for estimation and hypothesis testing of the HRF are developed. Simulations support the effectiveness of our proposed methods. When applied to an efMRI dataset from an emotional control study, our method reveals more meaningful findings than the popular methods offered by AFNI and FSL. (C) 2008 Elsevier B.V. All rights reserved.

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Ranald Roderick Macdonald (1945-2007) was an important contributor to mathematical psychology in the UK, as a referee and action editor for British Journal of Mathematical and Statistical Psychology and as a participant and organizer at the British Psychological Society's Mathematics, statistics and computing section meetings. This appreciation argues that his most important contribution was to the foundations of significance testing, where his concern about what information was relevant in interpreting the results of significance tests led him to be a persuasive advocate for the 'Weak Fisherian' form of hypothesis testing.

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An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation–climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America – 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

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In this paper, we discuss inferential aspects for the Grubbs model when the unknown quantity x (latent response) follows a skew-normal distribution, extending early results given in Arellano-Valle et al. (J Multivar Anal 96:265-281, 2005b). Maximum likelihood parameter estimates are computed via the EM-algorithm. Wald and likelihood ratio type statistics are used for hypothesis testing and we explain the apparent failure of the Wald statistics in detecting skewness via the profile likelihood function. The results and methods developed in this paper are illustrated with a numerical example.

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This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area. Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified. The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.

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The hypothetical extraction method (HEM) is used to extract a sector hypothetically from an economic system and examine the influence of this extraction on other sectors in the economy. Linkage measures based on the HEM become increasingly prominent. However, little construction linkage research applies the HEM. Using the recently published Organisation for Economic Co-operation and Development input-output database at constant prices, this research applies the HEM to the construction sector in order to explore the role of this sector in national economies and the quantitative interdependence between the construction sector and the remaining sectors. The output differences before and after the hypothetical extraction reflect the linkages of the construction sector. Empirical results show a declining trend of the total, backward and forward linkages, which confirms the decreasing role of the construction sector with economic maturity over the examined period from a new angle. Analytical results reveal that the unique nature of the construction sector and multifold external factors are the main reasons for the linkage difference between countries. Moreover, hypothesis-testing results consider statistically that the extraction structures employed in this research are appropriate to analyse the linkages of the construction sector.

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There has never been, and will never be, a randomized double-blind placebo-controlled trial demonstrating that exercise in youth, adulthood or old age reduces fragility or osteoporosis-related fractures in old age. The next level of evidence, a randomized, controlled but unblinded study with fractures as an end-point is feasible but has never been done. The basis for the belief that exercise reduces fractures is derived from lower levels of ‘evidence’, namely, retrospective and prospective observation cohort studies and case–control studies. These studies are at best hypothesis generating, never hypothesis testing. They are all subject to many systematic biases and should be interpreted with extreme scepticism. Surrogate measures of anti-fracture efficacy are the next level of evidence, such as the demonstration of a reduction in risk factors for falls, a reduction in falls, a reduction in fractures due to falls, an increase in peak bone size and mass, prevention of bone loss in midlife and restoration of bone mass and structure in old age.

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Human modification of landscapes typically results in many species being confined to small, isolated and degraded habitat fragments. While fragment size and isolation underpin many studies of modified landscapes, vegetation characteristics are less frequently incorporated. The relative influence of biogeographic (e.g. size, isolation) and vegetation parameters on assemblages is poorly understood, but critical for conservation management. In this study, a multiple hypothesis testing framework was used to determine the relative importance of biogeographic and vegetation parameters in explaining the occurrence of an assemblage of small mammals in 48 forest fragments in an agricultural landscape in south-eastern Australia. Fragment size and vegetation characteristics were consistently important predictors of occurrence across species. In contrast, fragment isolation was important for just one native species. Differing abilities of species to move through the landscape provide a reasonable explanation for these results. We conclude that for effective conservation of assemblages, it is important to: (1) consider differing responses of species to landscape change, and (2) move beyond a focus primarily on spatial attributes (size, isolation) to recognise that landscape change also has profound effects on habitat composition and quality.

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We consider a random design model based on independent and identically distributed pairs of observations (Xi, Yi), where the regression function m(x) is given by m(x) = E(Yi|Xi = x) with one independent variable. In a nonparametric setting the aim is to produce a reasonable approximation to the unknown function m(x) when we have no precise information about the form of the true density, f(x) of X. We describe an estimation procedure of non-parametric regression model at a given point by some appropriately constructed fixed-width (2d) confidence interval with the confidence coefficient of at least 1−. Here, d(> 0) and 2 (0, 1) are two preassigned values. Fixed-width confidence intervals are developed using both Nadaraya-Watson and local linear kernel estimators of nonparametric regression with data-driven bandwidths. The sample size was optimized using the purely and two-stage sequential procedures together with asymptotic properties of the Nadaraya-Watson and local linear estimators. A large scale simulation study was performed to compare their coverage accuracy. The numerical results indicate that the confi dence bands based on the local linear estimator have the better performance than those constructed by using Nadaraya-Watson estimator. However both estimators are shown to have asymptotically correct coverage properties.

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Purpose – This paper seeks to empirically examine the relationship between corporate image and customer satisfaction in the leisure services sector. It also aims to examine the mediating impact of employees and servicescape on this relationship.
Design/methodology/approach – Data were collected from a sample of 195 individuals who had visited an Australian zoological garden over a specified time period. Confirmatory factor analysis was used to test the validity of the measures, whilst structural equation modelling and multiple regression were used in hypothesis testing.
Findings – Findings reveal that corporate image has a significant positive relationship with customer satisfaction. Although the results indicate that the relationship between corporate image and customer satisfaction is not mediated by either servicescape or employees, they imply that corporate image and employees directly influence customer satisfaction.
Research limitations/implications – A single-case study design was implemented, limiting the generalisability of the findings. This provides an opportunity for replication of the model in other leisure services environments and services contexts outside the leisure services industry.
Practical implications – The findings reinforce the need for leisure services operators to prioritise the development of a strong, clear corporate image. The extended analysis illustrates that the disaggregated dimensions of corporate image are valuable to consider in terms of directing managerial strategy. Employees and servicescape are key aspects of the service offer on which management needs to focus to ensure that their desired corporate image is communicated and reinforced.
Originality/value – This study addresses an identified need to further examine the relationship between corporate image and customer satisfaction. It also contributes to corporate branding research by broadening the conceptualisation of the corporate image construct. Moreover, this study contributes to the corporate image literature by examining the mediating factors of employees and servicescape.

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Recent developments in ecological statistics have reached behavioral ecology, and an increasing number of studies now apply analytical tools that incorporate alternatives to the conventional null hypothesis testing based on significance levels. However, these approaches continue to receive mixed support in our field. Because our statistical choices can influence research design and the interpretation of data, there is a compelling case for reaching consensus on statistical philosophy and practice. Here, we provide a brief overview of the recently proposed approaches and open an online forum for future discussion (https://bestat.ecoinformatics.org/). From the perspective of practicing behavioral ecologists relying on either correlative or experimental data, we review the most relevant features of information theoretic approaches, Bayesian inference, and effect size statistics. We also discuss concerns about data quality, missing data, and repeatability. We emphasize the necessity of moving away from a heavy reliance on statistical significance while focusing attention on biological relevance and effect sizes, with the recognition that uncertainty is an inherent feature of biological data. Furthermore, we point to the importance of integrating previous knowledge in the current analysis, for which novel approaches offer a variety of tools. We note, however, that the drawbacks and benefits of these approaches have yet to be carefully examined in association with behavioral data. Therefore, we encourage a philosophical change in the interpretation of statistical outcomes, whereas we still retain a pluralistic perspective for making objective statistical choices given the uncertainties around different approaches in behavioral ecology. We provide recommendations on how these concepts could be made apparent in the presentation of statistical outputs in scientific papers.

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This study assesses the effects of mentoring and organisational ethical climate (OEC) on the organisational and professional commitment (PC) of early career accountants (ECAs) (i.e. accounting graduate recruits with three or less years of working experience). The empirical data are based on a questionnaire survey from 86 ECAs in Australian public accounting firms, and hypothesis testing utilises partial least squares analysis. Our results indicate when a career development style of mentoring is adopted there is greater organisational as well as PC. By contrast, a social support mentoring style has no significant impact on organisational commitment (OC) and a negative effect on PC. Further, our data also reveal OEC to be positively associated with OC, and OC in turn having a positive impact on PC. The results imply that fostering a career-focused mentoring environment and an OEC can increase an ECA's OC and PC. These results have various implications for human resource management at both the accounting firm and professional levels.