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作者：Kosmidis, Ioannis; Firth, David
作者单位：University of London; University College London; University of Warwick
摘要：For the parameters of a multinomial logistic regression, it is shown how to obtain the bias-reducing penalized maximum likelihood estimator by using the equivalent Poisson log-linear model. The calculation needed is not simply an application of the Jeffreys prior penalty to the Poisson model. The development allows a simple and computationally efficient implementation of the reduced-bias estimator, using standard software for generalized linear models.
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作者：Li, Zhiguo; Murphy, Susan A.
作者单位：Duke University; University of Michigan System; University of Michigan
摘要：Two-stage randomized trials are growing in importance in developing adaptive treatment strategies, i.e. treatment policies or dynamic treatment regimes. Usually, the first stage involves randomization to one of the several initial treatments. The second stage of treatment begins when an early nonresponse criterion or response criterion is met. In the second-stage, nonresponding subjects are re-randomized among second-stage treatments. Sample size calculations for planning these two-stage rando...
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作者：Farewell, D. M.
作者单位：Cardiff University
摘要：We consider solutions to generalized estimating equations with singular working correlation matrices, of which the estimator of Diggle et al. (2007) is a special case. We give explicit conditions for consistent estimation when the pattern of observations may be informative. In such cases, simulations reveal reduced bias and reduced mean squared error compared with existing alternatives. A study of peritoneal dialysis is used to illustrate the methodology.
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作者：Antognini, Alessandro Baldi; Giovagnoli, Alessandra
作者单位：University of Bologna
摘要：In recent years, several authors have investigated response-adaptive allocation rules for comparative clinical trials, in order to favour, at each stage of the trial, the treatment that appears to be best. In this paper, we define admissible allocations, namely treatment assignments that cannot be simultaneously improved upon with respect to both a specific design criterion, reflecting the inferential properties of the experiment, and the proportion of patients assigned to the best treatment o...
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作者：Mueller, Hans-Georg; Yao, Fang
作者单位：University of California System; University of California Davis; University of Toronto
摘要：We consider the problem of estimating functional derivatives and gradients in the framework of a regression setting where one observes functional predictors and scalar responses. Derivatives are then defined as functional directional derivatives that indicate how changes in the predictor function in a specified functional direction are associated with corresponding changes in the scalar response. For a model-free approach, navigating the curse of dimensionality requires the imposition of suita...
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作者：Wang, Huixia Judy; Zhou, Xiao-Hua
作者单位：North Carolina State University; US Department of Veterans Affairs; Veterans Health Administration (VHA); Vet Affairs Puget Sound Health Care System
摘要：We propose a new approach for analyzing skewed and heteroscedastic health care cost data through regression of the conditional quantiles of the transformed cost. Using the appealing equivariance property of quantiles to monotone transformations, we propose a distribution-free estimator of the conditional mean cost on the original scale. The proposed method is extended to a two-part heteroscedastic model to account for zero costs commonly seen in health care cost studies. Simulation studies ind...
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作者：Ferraty, F.; Hall, P.; Vieu, P.
作者单位：Universite de Toulouse; Universite Toulouse III - Paul Sabatier; University of Melbourne
摘要：We suggest a way of reducing the very high dimension of a functional predictor, X, to a low number of dimensions chosen so as to give the best predictive performance. Specifically, if X is observed on a fine grid of design points t(1),..., t(r), we propose a method for choosing a small subset of these, say t(i1),..., t(ik), to optimize the prediction of a response variable, Y. The values t(ij) are referred to as the most predictive design points, or covariates, for a given value of k, and are ...
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作者：Yao, Fang; Mueller, Hans-Georg
作者单位：University of Toronto; University of California System; University of California Davis
摘要：We extend the common linear functional regression model to the case where the dependency of a scalar response on a functional predictor is of polynomial rather than linear nature. Focusing on the quadratic case, we demonstrate the usefulness of the polynomial functional regression model, which encompasses linear functional regression as a special case. Our approach works under mild conditions for the case of densely spaced observations and also can be extended to the important practical situat...
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作者：Hall, Peter; Xue, Jing-Hao
作者单位：University of Melbourne; University of London; University College London
摘要：In standard parametric classifiers, or classifiers based on nonparametric methods but where there is an opportunity for estimating population densities, the prior probabilities of the respective populations play a key role. However, those probabilities are largely ignored in the construction of high-dimensional classifiers, partly because there are no likelihoods to be constructed or Bayes risks to be estimated. Nevertheless, including information about prior probabilities can reduce the overa...
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作者：Abramovich, Felix; Grinshtein, Vadim; Petsa, Athanasia; Sapatinas, Theofanis
作者单位：Tel Aviv University; Open University Israel; University of Cyprus
摘要：We consider the problem of estimating the unknown response function in the Gaussian white noise model. We first utilize the recently developed Bayesian maximum a posteriori testimation procedure of Abramovich et al. (2007) for recovering an unknown high-dimensional Gaussian mean vector. The existing results for its upper error bounds over various sparse l(p)-balls are extended to more general cases. We show that, for a properly chosen prior on the number of nonzero entries of the mean vector, ...
