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作者：HOUGAARD, P
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作者：WESTFALL, P
摘要：A locally optimal test for a null variance ratio is considered in the context of the one-way random effects model, when normality is assumed. Using an asymptotic design sequence with an increasing number of groups without bounded but unequal sizes, this test has the correct asymptotic level of significance for nonnormal data, property which is not shared by the competing Wald test. Asymptotic power calculations demonstrate that the locally optimal test may be more powerful than the Wald test e...
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作者：ASSAF, D; RITOV, Y
摘要：Let X1, X2,...be such that X1,...,XT-1 have the distribution Fo, while XT, XT+1,... have the distribution F1. Think of X1, X2,... as samples from large batches and suppose T has a prior geometric distribution. Sampling from each batch is assumed to give rise to a Brownian motion process and we are interested in both an optimal sampling scheme and an optimal stopping time to detect the changepoint T. The suggested procedure may roughly be described as a sequence of sequential probability ratio ...
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作者：BARLEV, SK; ENIS, P
作者单位：State University of New York (SUNY) System; University at Buffalo, SUNY
摘要：A simple method for obtaining a class of variance stabilizing transformations from a given normalizing transformation is presented. The method is based on Curtiss''s (1943) classical results on such transformations. Illustrations are given for a Poisson variate.
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作者：ZEGER, SL
摘要：This paper discusses a model for regression analysis with a time series of counts. Correlation is assumed to arise from an unobservable process added to the linear predictor in a log linear model. An estimating equation approach used for parameter estimation leads to an iterative weighted and filtered least-squares algorithm. Asymptotic properties for the regression coefficients are presented. We illustrate the technique with an analysis of trends in U.S. polio incidence since 1970.
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作者：GREENACRE, MJ
摘要：A generalization of correspondence analysis to multivariate categorical data is proposed, where all two-way contingency tables of a set of categorical variables are simultaneously fitted by weighted least-squares. An alternating least-squares algorithm is developed to perform the fitting. This technique has a number of advantages over the usual generalization known as multiple correspondence analysis. It is also an analogue of least-squares factor analysis for categorical data.
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作者：BARLOW, WE; PRENTICE, RL
作者单位：Fred Hutchinson Cancer Center
摘要：Several possible definitions of residuals are given for relative risk regression with time-varying covariates. Each such residual has a representation as an estimator of a stochastic integral with respect to the martingale arising from a subject''s failure time counting process. Previously proposed residuals for individual study subjects and for specific time points are shown to be special cases of this definition, as are previously derived regression diagnostics. An illustration and various g...
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作者：KUK, AYC
摘要：We consider sampling with probability proportional to size or aggregate size and derive a number of estimators of the finite population distribution function. The estimators are compared theoretically and empirically. By inverting the distribution function estimators, we obtain estimators of the finite population median. The performance of these median estimators are investigated.
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作者：MUKERJEE, H
摘要：There is an extensive literature on inferences from independent random samples about several normal means under order restrictions. The purpose of this note is to point out these results have very simple generalizations to one repeated measures model.
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作者：CHOI, YJ; SEVERO, NC
摘要：Hill and Severo (1969) and Kryscio (1972) present approximations to the maximum likelihood estimator of the infection rate of the simple stochastic epidemic model. These approximations, valid under some restrictions on the data set, use a table published by Hill and Severo (1969). We give here an algebraically simpler approximation, which does not use an auxiliary table and may be applied to all data sets.
