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作者：Allen, AS; Satten, GA; Tsiatis, AA
作者单位：Duke University; Duke University; Centers for Disease Control & Prevention - USA; North Carolina State University
摘要：Modelling human genetic variation is critical to understanding the genetic basis of complex disease. The Human Genome Project has discovered millions of binary DNA sequence variants, called single nucleotide polymorphisms, and millions more may exist. As coding for proteins takes place along chromosomes, organisation of polymorphisms along each chromosome, the haplotype phase structure, may prove to be most important in discovering genetic variants associated with disease. As haplotype phase i...
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作者：Ritz, C; Skovgaard, IM
作者单位：University of Copenhagen
摘要：For submodels of an exponential family, we consider likelihood ratio tests for hypotheses that render some parameters nonidentifiable. First, we establish the asymptotic equivalence between the likelihood ratio test and the score test. Secondly, the score-test representation is used to derive the asymptotic distribution of the likelihood ratio test. These results are derived for general submodels of an exponential family without assuming compactness of the parameter space. We then exemplify th...
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作者：Marshall, AW; Olkin, I
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作者：Cheung, YK
作者单位：Columbia University
摘要：This paper studies the coherence conditions of dose-finding methods in the context of phase I clinical trials, where the objective is to estimate a targeted quantile of the unknown dose-toxicity curve. Most phase I methods are outcome-adaptive, and thus escalate or de-escalate doses for future patients based on the previous observations. An escalation for a new patient is said to be coherent only when the previous patient does not show sign of toxicity. Likewise, a de-escalation is coherent on...
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作者：Lam, KF; Xue, HQ
作者单位：University of Hong Kong; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS
摘要：This paper considers the analysis of current status data with a cured proportion in the population using a mixture model that combines a logistic regression formulation for the probability of cure with a semiparametric regression model for the time to occurrence of the event. The semiparametric regression model belongs to the flexible class of partly linear models that allows one to explore the possibly nonlinear effect of a certain covariate on the response variable. A sieve maximum likelihoo...
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作者：Lawless, JF; Fredette, M
作者单位：University of Waterloo; Universite de Montreal; HEC Montreal
摘要：We consider parametric frameworks for the prediction of future values of a random variable Y, based on previously observed data X. Simple pivotal methods for obtaining calibrated prediction intervals are presented and illustrated. Frequentist predictive distributions are defined as confidence distributions, and their utility is demonstrated. A simple pivotal-based approach that produces prediction intervals and predictive distributions with well-calibrated frequentist probability interpretatio...
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作者：Crainiceanu, C; Ruppert, D; Claeskens, G; Wand, MP
作者单位：Johns Hopkins University; Cornell University; KU Leuven; University of New South Wales Sydney
摘要：Penalised-spline-based additive models allow a simple mixed model representation where the variance components control departures from linear models. The smoothing parameter is the ratio of the random-coefficient and error variances and tests for linear regression reduce to tests for zero random-coefficient variances. We propose exact likelihood and restricted likelihood ratio tests for testing polynomial regression versus a general alternative modelled by penalised splines. Their spectral dec...
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作者：Uno, H; Tian, L; Wei, LJ
作者单位：Northwestern University; Harvard University
摘要：Suppose that, under a two-level hierarchical model, the distribution of the vector of random parameters is known or can be estimated well. The data are generated via a fixed, but unobservable, realisation of the vector. We derive the smallest confidence region for a specific component of this random vector under a joint Bayesian/frequentist paradigm. On average this optimal region can be much smaller than the corresponding Bayesian highest posterior density region. The new estimation procedure...
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作者：Qin, J; Zhang, B
作者单位：National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID); University System of Ohio; University of Toledo
摘要：Marginal likelihood and conditional likelihood are often used for eliminating nuisance parameters. For a parametric model, it is well known that the full likelihood can be decomposed into the product of a conditional likelihood and a marginal likelihood. This property is less transparent in a nonparametric or semiparametric likelihood setting. In this paper we show that this nice parametric likelihood property can be carried over to the empirical likelihood world. We discuss applications in ca...
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作者：Chen, KN; Jin, ZZ
作者单位：Hong Kong University of Science & Technology; Columbia University
摘要：This paper proposes a classical weighted least squares type of local polynomial smoothing for the analysis of clustered data, with the key idea of using generalised inverses of correlation matrices. The estimator has a simple closed-form expression. Simplicity is achieved also for nonparametric generalised linear models with arbitrary link function via a transformation. Our approach can be characterised by 'local observations with local variances', which yields intuitively correct results in t...
