829 resultados para Social hypothesis testing
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Exam questions and solutions in PDF
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Exercises and solutions in PDF
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Lecture notes in PDF
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Exam questions and solutions in LaTex. Diagrams for the questions are all together in the support.zip file, as .eps files
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Exercises and solutions in LaTex
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PowerPoint slides for Confidence Intervals. Examples are taken from the Medical Literature
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Objetivos: Determinar si existe diferencia en la ganancia interdialítica entre los pacientes al ser tratados con flujo de dializado (Qd) de 400 mL/min y 500 mL/min. Diseño: Se realizó un estudio de intervención, cruzado, aleatorizado, doble ciego en pacientes con enfermedad renal crónica en hemodiálisis para determinar diferencias en la ganancia de peso interdialítica entre los pacientes tratados con flujo de dializado (Qd) de 400 ml/min y 500 ml/min. Pacientes: Se analizaron datos de 46 pacientes en hemodiálisis crónica con Qd de 400 ml/min y 45 con Qd de 500 ml/min. Análisis: La prueba de hipótesis para evaluar diferencias en la ganancia interdialítica y las otras variables entre los grupos se realizó mediante la prueba T para muestras pareadas. Para el análisis de correlación se calculó el coeficiente de Pearson. Resultados: No hubo diferencia significativa en ganancia interdialítica usando Qd de 400 ml/min vs 500 ml/min (2.37 ± 0.7 vs 2.41 ± 0.6, p=0.41) ni en Kt/V (1.57 ± 0.25 vs 1.59 ± 0.23, p = 0.45), potasio (4.9 ± 1.1 vs 5.1 ± 1.0, p=0.45), fosforo (4.5 ± 1.2 vs 4.4 ± 1.2, p=0.56) o hemoglobina (11.3 ± 1.8 vs 11.3 ± 1.6, p=0.96). Conclusiones: En pacientes con peso ≤ 65 Kg el uso de Qd de 400 ml/min no se asocia con menor ganancia interdialítica de peso. No hay diferencia en la eficiencia de diálisis lo que sugiere que es una intervención segura a corto plazo.
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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.
Big Decisions and Sparse Data: Adapting Scientific Publishing to the Needs of Practical Conservation
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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.