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作者：Bandeen-Roche, K; Liang, KY
作者单位：Johns Hopkins University
摘要：There has been much research on analysing multivariate failure times, but little that has accommodated failures that arise in the presence of a competing failure process. This paper studies the problem of describing associations among times to such failures. It proposes a modified conditional hazard ratio measure of association that is tailored to competing risks data, develops frailty models and a nonparametric method for describing the proposed measure, and contrasts estimation by proposed m...
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作者：Martinussen, T; Scheike, TH
作者单位：University of Copenhagen; University of Copenhagen
摘要：We present a new additive-multiplicative hazard model which consists of two components. The first component contains additive covariate effects through an additive Aalen model while the second component contains multiplicative covariate effects through a Cox regression model. The Aalen model allows for time-varying covariate effects, while the Cox model allows only a common time-dependence through the baseline. Approximate maximum likelihood estimators are derived by solving the simultaneous s...
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作者：Carota, C; Parmigiani, G
作者单位：University of Turin; Johns Hopkins University
摘要：We introduce a class of Bayesian semiparametric models for regression problems in which the response variable is a count. Our goal is to provide a flexible, easy-to-implement and robust extension of generalised linear models, for datasets of moderate or large size. Our approach is based on modelling the distribution of the response variable using a Dirichlet process, whose mean distribution function is itself random and is given a parametric form, such as a generalised linear model. The effect...
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作者：Grabarnik, P; Chiu, SN
作者单位：Russian Academy of Sciences; Pushchino Scientific Center for Biological Research (PSCBI) of the Russian Academy of Sciences; Institute of Physicohemical & Biological Problems of Soil Science; Hong Kong Baptist University
摘要：A goodness-of-fit test statistic for spatial point processes is proposed and shown to have an asymptotic chi-squared distribution if the underlying point process is Poisson. Simulations demonstrate that the test, when testing for complete spatial randomness, is more sensitive to mixtures of regular and clustered point processes than the tests using the nearest neighbour distance distribution, the second- or third-order characteristics.
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作者：Severini, TA
作者单位：Northwestern University
摘要：In a parametric model the maximum likelihood estimator of a parameter of interest may be viewed as the solution to the equation l'(p)(psi) = 0, where l(p) denotes the profile loglikelihood function. It is well known that the estimating function l'p (psi) is not unbiased and that this bias can, in some cases, lead to poor estimates of psi. An alternative approach is to use the modified profile likelihood function, or an approximation to the modified profile likelihood function, which yields an ...
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作者：Gabriel, KR
作者单位：University of Rochester
摘要：The present paper examines proportional goodness of fit to variables recorded on individuals, the variances and covariances of the variables, and the form and distances between individuals. No single plot displays all three optimally in the sense of least squares. However, even aspects which are non-optimally fitted by biplots and Benzecri plots often closely preserve the optimal fit. This is shown by means of a preservation-of-fit function which depends on the type of display and on the ratio...
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作者：DiCiccio, TJ; Monti, AC
作者单位：Cornell University; University of Sannio
摘要：This paper concerns high-order inference for scalar parameters that are estimated by functions of multivariate M-estimators. Asymptotic formulae for the bias and skewness of the studentised statistic are derived. Although these formulae appear complicated, they can be evaluated easily by using matrix operations and numerical differentiation. Various methods for constructing second-order accurate confidence limits are discussed, including a method based on skewness-reducing transformations and ...
