48 research outputs found

    A comparison of missing data methods for hypothesis tests of the treatment effect in substance abuse clinical trials: a Monte-Carlo simulation study

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    <p>Abstract</p> <p>Background</p> <p>Missing data due to attrition are rampant in substance abuse clinical trials. However, missing data are often ignored in the presentation of substance abuse clinical trials. This paper demonstrates missing data methods which may be used for hypothesis testing.</p> <p>Methods</p> <p>Methods involving stratifying and weighting individuals based on missing data pattern are shown to produce tests that are robust to missing data mechanisms in terms of Type I error and power. In this article, we describe several methods of combining data that may be used for testing hypotheses of the treatment effect. Furthermore, illustrations of each test's Type I error and power under different missing data percentages and mechanisms are quantified using a Monte-Carlo simulation study.</p> <p>Results</p> <p>Type I error rates were similar for each method, while powers depended on missing data assumptions. Specifically, power was greatest for the weighted, compared to un-weighted methods, especially for greater missing data percentages.</p> <p>Conclusion</p> <p>Results of this study as well as extant literature demonstrate the need for standards of design and analysis specific to substance abuse clinical trials. Given the known substantial attrition rates and concern for the missing data mechanism in substance abuse clinical trials, investigators need to incorporate missing data methods a priori. That is, missing data methods should be specified at the outset of the study and not after the data have been collected.</p

    Adaptive Radial Basis Function Methods for Pricing Options Under Jump-Diffusion Models

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    The aim of this paper is to show that option prices in jump-diffusion models can be computed using meshless methods based on radial basis function (RBF) interpolation instead of traditional mesh-based methods like finite differences or finite elements. The RBF technique is demonstrated by solving the partial integro-differential equation for American and European options on non-dividend-paying stocks in the Merton jump-diffusion model, using the inverse multiquadric radial basis function. The method can in principle be extended to Lévy-models. Moreover, an adaptive method is proposed to tackle the accuracy problem caused by a singularity in the initial condition so that the accuracy in option pricing in particular for small time to maturity can be improved

    Analýza podmíněnosti radiálních bázových funkcí

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    Globální radiální bázové funkce obecně vedou ke špatně podmíněné soustavě lineárních rovnic. Tento příspěvek analyzuje podmíněnost Gaussovy a „Thin Plate Spline“ (TPS) funkcí. Experimenty ukázaly závislost na tvarovém parametru a počtu bodů. Tato závislost lze popsat analyticky.The global RBFs lead to an ill-conditioned system of linear equations, in general. This contribution analyzes conditionality of the Gauss and the Thin Plate Spline (TPS) functions. Experiments made proved dependency of the shape parameter and number of points, which can be described as an analytical function

    Nová strategie pro aproximaci rozptýlených dat s využitím radiálních bázových funkcí respektující body inflexe

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    Aproximace rozptýlených dat je známá technika v počítačové vědě. Navrhujeme novou strategii pro umístění radiálních základních funkcí s ohledem na inflexní body. Umístění radiální základní funkce má velký vliv na kvalitu aproximace. Z tohoto důvodu navrhujeme novou strategii pro umístění radiálních základních funkcí s ohledem na vlastnosti aproximované funkce, včetně extrémních a inflexních bodů. Naše experimentální výsledky prokázaly vysokou kvalitu navrhovaného přístupu a vysokou kvalitu konečné aproximace.The approximation of scattered data is known technique in computer science. We propose a new strategy for the placement of radial basis functions respecting points of inflection. The placement of radial basis functions has a great impact on the approximation quality. Due to this fact we propose a new strategy for the placement of radial basis functions with respect to the properties of approximated function, including the extreme and the inflection points. Our experimental results proved high quality of the proposed approach and high quality of the final approximation
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