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241.
The main goal of phase I cancer clinical trials is to determine the highest dose of a new therapy associated with an acceptable level of toxicity for the use in a subsequent phase II trial. The continual reassessment method (CRM) [O’Quigley, J., Pepe, M., Fisher, L., 1990. Continual reassessment method: a practical design for phase I clinical trials in cancer. Biometrics 46, 33–48] and escalation with overdose control (EWOC) [Babb, J., Rogatko, A., Zacks, S., 1998. Cancer phase I clinical trials: efficient dose escalation with overdose control. Statist. Med. 17 (10), 1103–1120] are two model-based designs used for phase I cancer clinical trials. A few modifications of the (original) CRM and EWOC have been made by many authors. In this paper, we show how CRM and EWOC can be unified and present a hybrid design. We study the characteristics of the approach of the hybrid design. The comparisons of the three designs (CRM, EWOC, and the hybrid design) are presented by convergence rates and overdose proportions. The simulation results show that the hybrid design generally has faster convergence rates than EWOC and smaller overdose proportions than CRM, especially when the true maximum tolerated dose (MTD) is above the mid-level of the dose range considered. The performance of these three designs is also evaluated in terms of sensitivity to outliers. 相似文献
242.
In this paper we discuss constructing confidence intervals based on asymptotic generalized pivotal quantities (AGPQs). An AGPQ associates a distribution with the corresponding parameter, and then an asymptotically correct confidence interval can be derived directly from this distribution like Bayesian or fiducial interval estimates. We provide two general procedures for constructing AGPQs. We also present several examples to show that AGPQs can yield new confidence intervals with better finite-sample behaviors than traditional methods. 相似文献
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244.
Abstract. Collapsibility means that the same statistical result of interest can be obtained before and after marginalization over some variables. In this paper, we discuss three kinds of collapsibility for directed acyclic graphs (DAGs): estimate collapsibility, conditional independence collapsibility and model collapsibility. Related to collapsibility, we discuss removability of variables from a DAG. We present conditions for these three different kinds of collapsibility and relationships among them. We give algorithms to find a minimum variable set containing a variable subset of interest onto which a statistical result is collapsible. 相似文献
245.
Nuoo-Ting Molitor Nicky Best Chris Jackson Sylvia Richardson 《Journal of the Royal Statistical Society. Series A, (Statistics in Society)》2009,172(3):615-637
Summary. Data in the social, behavioural and health sciences frequently come from observational studies instead of controlled experiments. In addition to random errors, observational data typically contain additional sources of uncertainty such as missing values, unmeasured confounders and selection biases. Also, the research question is often different from that which a particular source of data was designed to answer, and so not all relevant variables are measured. As a result, multiple sources of data are often necessary to identify the biases and to inform about different aspects of the research question. Bayesian graphical models provide a coherent way to connect a series of local submodels, based on different data sets, into a global unified analysis. We present a unified modelling framework that will account for multiple biases simultaneously and give more accurate parameter estimates than standard approaches. We illustrate our approach by analysing data from a study of water disinfection by-products and adverse birth outcomes in the UK. 相似文献
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247.
古今文学演变与中国文学史研究之间的内在关联,大体可以从四个层面来描述:"中国文学史"这样一种著述方式是伴随着古今文学的转型而产生的;现代的纯文学观深刻影响了20世纪90年代之前的"中国文学史"撰写;对古今文学之异的清醒认识是编年体文学史兴起的契机;中国文学史研究中的"古今"问题的核心是如何处理主体性与客观性的关系.我们的讨论即从这四个方面展开. 相似文献
248.
文学古今演变的临界点之辨 总被引:1,自引:1,他引:0
中国文学古今演变是一个富有活力的学术命题,自复旦大学章培恒教授首倡以来,相关的学术探索新见迭出,取得了不俗的成绩. 相似文献
249.
Peter Hall Tapabrata Maiti 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2009,71(3):703-718
Summary. We develop a general non-parametric approach to the analysis of clustered data via random effects. Assuming only that the link function is known, the regression functions and the distributions of both cluster means and observation errors are treated non-parametrically. Our argument proceeds by viewing the observation error at the cluster mean level as though it were a measurement error in an errors-in-variables problem, and using a deconvolution argument to access the distribution of the cluster mean. A Fourier deconvolution approach could be used if the distribution of the error-in-variables were known. In practice it is unknown, of course, but it can be estimated from repeated measurements, and in this way deconvolution can be achieved in an approximate sense. This argument might be interpreted as implying that large numbers of replicates are necessary for each cluster mean distribution, but that is not so; we avoid this requirement by incorporating statistical smoothing over values of nearby explanatory variables. Empirical rules are developed for the choice of smoothing parameter. Numerical simulations, and an application to real data, demonstrate small sample performance for this package of methodology. We also develop theory establishing statistical consistency. 相似文献
250.
本文对近年来民俗志书写理论和实践上的一些新探索作了初步梳理,指出了"标志性文化统领式民俗志"对于创新民俗志书写模式、增强民俗志书写主位视角和对话功能的意义以及"感受之学"在探寻民俗志独特学科品格上做出的探索和努力. 相似文献