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作者：Chang, SH; Wang, MC
作者单位：National Taiwan University; Johns Hopkins University
摘要：Recurrence time data can be regarded as a specific type of correlated survival data in which recurrent event times of a subject are stochastically ordered. Given the ordinal nature of recurrence times, this article focuses on conditional regression analysis. A semiparametric hazards model, including the structural and episode-specific parameters, is proposed for recurrence time data. In this model the order of episodes serves as the stratification variable. Estimation of the structural paramet...
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作者：Scharfstein, DO; Rotnitzky, A; Robins, JM
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作者：Bonetti, M; Cole, BF; Gelber, RD
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Dartmouth College; Harvard University; Harvard T.H. Chan School of Public Health; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Harvard University; Harvard Medical School
摘要：Quality-of-life outcomes collected during clinical trials often have considerable amounts of missing data, which, if not appropriately accounted for, may lead to bias in inferences. We introduce a method-of-moments (MM) estimating procedure for a model designed to handle nonignorable missingness arising in categorical data measured on independent populations. The missingness mechanism is assumed to be the same across the populations. We derive necessary and sufficient conditions for the identi...
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作者：Théberge, A
作者单位：Statistics Canada
摘要：Estimators from the family of calibration estimators are often used when auxiliary information about a population is available. By viewing calibration as an algebraic problem, this article extends the: calibration technique to estimate population parameters other than totals and means, and also extends the technique to the case where there is no solution to the calibration equation. These extensions permit the development of estimators for small domains that have a synthetic component and yet ...
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作者：Liu, JS; Neuwald, AF; Lawrence, CE
作者单位：Stanford University; Cold Spring Harbor Laboratory; State University of New York (SUNY) System; Wadsworth Center
摘要：The alignment of multiple homologous biopolymer sequences is crucial in research on protein modeling and engineering, molecular evolution, and prediction in terms of both gene function and gene product structure. In this article we provide a coherent view of the two recent models used for multiple sequence alignment-the hidden Markov model (HMM) and the block-based motif model-to develop a set of new algorithms that have both the sensitivity of the block-based model and the flexibility of the ...
