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作者：MEESTER, SG; LOCKHART, RA
作者单位：University of Toronto; Simon Fraser University
摘要：Goodness-of-fit tests are provided for the assumption of homoscedastic normal errors in experimental designs where the number of fitted parameters is large. Asymptotic critical points are given for the Cramer-von Mises statistic, Watson''s statistic and the Anderson-Darling statistic. An expansion of the covariance function of the empirical process of standardized residuals is given. The corresponding weak convergence result is established for one-way layouts when the number of parameters grow...
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作者：HINKLEY, DV
摘要：Lawrance''s (1987) results concerning tests for transformation in regression are extended to models where response and mean may both be transformed. It is also suggested (i) that the methods of Lawrance and of Atkinson (1982) lead to statistics with near-perfect correlation, and (ii) that observed and expected informations may have considerably different effects as standardizations of the score statistic.
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作者：LI, WK
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作者：KOTT, PS
摘要：This paper discusses a model-based finite population correction term for estimating the model and design variances of the Horvitz-Thompson estimator under the usual model.
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作者：KIM, KM
摘要：Siegmund (1978) has developed a procedure for estimation following a closed sequential test, known as the repeated significance tests. Here a more elaborate approximation is proposed for a wider class of closed sequential tests. The major goal is to account for the excess over boundary in addition to the stopping time when the sequential test is terminated. Some hypothetical examples are used for comparing the two approximations. To investigate the properties of these procedures further, simul...
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作者：HALL, P; MARTIN, MA
摘要：We propose a single unifying approach to bootstrap resampling, applicable to a very wide range of statistical problems. It enables attention to be focused sharply on one or more characteristics which are of major importance in any particular problem, such as coverage error or length for confidence intervals, or bias for point estimation. Our approach leads easily and directly to a very general form of bootstrap iteration, unifying and generalizing present disparate accounts of this subject. It...
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作者：ROSNER, GL; TSIATIS, AA
作者单位：Harvard University; Harvard T.H. Chan School of Public Health
摘要：With interest in designing group sequential clinical trials increasing, methodology for analysing the data arising in such trials is needed. We discuss several approaches to constructing confidence intervals for the parameter of interest in a group sequential trial after the trial has ended. We compare these methods to one already in the literature and point out interesting differences.
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作者：FRASER, DAS; REID, N
作者单位：University of Toronto
摘要：A one-dimensional conditional procedure defines a partition of the sample space into curves which can be represented by means of a unit vector field. A formula is given for the conditional distribution in terms of local properties of the vector field. Conditions are developed for reducing the first-order effects of nuisance parameters and reproducing to higher order the likelihood changes for the parameter of interest. The emphasis is on extending exponential family methods after locally appro...
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作者：MEHTA, CR; PATEL, NR; WEI, LJ
作者单位：Indian Institute of Management (IIM System); Indian Institute of Management Ahmedabad; University of Michigan System; University of Michigan
摘要：In a clinical trial comparing two treatments, suppose that subjects are assigned sequentially to the treatment groups by a restricted randomization rule. Under the randomization model, an efficient recursive algorithm is provided to generate the exact permutational distribution for linear rank statistics, given the final imbalance between the number of patients in the two groups. If only the significance level of the test is required, the efficiency of the algorithm can be improved significant...
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作者：RAFTERY, AE
摘要：A hierarchical Bayes approach to the problem of estimating N in the binomial distribution is presented. This provides a simple and flexible way of specifying prior information, and also allows a convenient representation of vague prior knowledge. It yields solutions to the problems of interval estimation, prediction and decision making, as well as that of point estimation. The Bayes estimator compares favourably with the best, previously proposed, point estimators in the literature.
