Bayesian Survival Analysis Using Bernstein Polynomials

Abstract.  Bayesian survival analysis of right-censored survival data is studied using priors on Bernstein polynomials and Markov chain Monte Carlo methods. These priors easily take into consideration geometric information like convexity or initial guess on the cumulative hazard functions, select only smooth functions, can have large enough support, and can be easily specified and generated. Certain frequentist asymptotic properties of the posterior distribution are established. Simulation studies indicate that these Bayes methods are quite satisfactory.     

Body Weight and Matching With a Physically Attractive Romantic Partner

Matching and attribute trade are two perspectives used to explain mate selection. We investigated patterns of matching and trade, focusing on obesity, using Add Health Romantic Pair data (N = 1,405 couples). Obese individuals, relative to healthy weight individuals, were less likely to have physically attractive partners, with this disadvantage greater for women than men, and greater for White women than Black women. Additional education, a more attractive personality, and better grooming increased the probability of having a physically attractive partner and offset the disadvantage of obesity for some individuals. Unexpectedly, we found women, like men, trade education for their partners’ physical attractiveness. Despite evidence of attribute trade, matching with respect to physical characteristics was the dominant mate selection pattern.     

MULTIVARLYTE ANALYSIS OF CLUSTERED SURVEY DATA: TESTING EQUALITY OF COVARLANCE MATRICES

The problem of testing the hypothesis of equality of covariance matrices in the presence of two-stage sampling is considered. Asymptotic test procedures based on linearization, grouping and jackknifing with or without transformation are proposed. The finite sample properties of these procedures are investigated in sampling experiments both from simulated known distributions and from a natural population.     

Confidence bands from censored samples

Several types of asymptotic confidence bands have been proposed in the literature when the data are randomly censored on the right. Introducing new classes of bands, we place the old bands and their relationship to one another within a comprehensive theory of bands. A thorough analysis yields narrower bands and two kinds of modifications which are asymptotically distribution- and censor-free. One of these is useful when the interval on which the bands are constructed is predetermined and the width of the bands is random; the other, when there is a predetermined bound on the width and the interval is random. We illustrate our bands on the Szeged pacemaker data. These methods also provide a general modification of the Kolmogorov band in the uncensored case.     

Customer Perceptions of Agency Risk Communication

A government agency commissioned a baseline study of how its customers view the agency's risk information. The 70% response rate to a mail survey allows analysis by subgroups representing customers'primary interests. Although this agency traditionally has been responsible for ensuring plant and animal health at the farm gate (or where imported), responses emphasized emerging customer concerns about the environment and human health. Customers think many risk communication activities are important, but that the agency is not especially effective in conducting those activities. Customers are moderately satisfied with much of the risk information they receive, although many have little contact from or interaction with the agency. Customers identified other sources they use, which suggest potentially effective channels for this agency's risk messages. The study provides a baseline for measuring change in the agency's risk communication effectiveness. It also can be a model when other organizations plan their own risk communication evaluations.     

ANALYSIS OF DOUBLY CENSORED DATA AND THE HIV INCUBATION PERIOD DISTRIBUTION IN WESTERN AUSTRALIA

The paper analyses the distribution of times from HIV seroconversion to the first AIDS defining illness for a subcohort of the Western Australian HIV Cohort Study for whom the seroconversion date is known to fall within a calendar time window. The analysis is based on a generalised gamma model for the incubation times and a piecewise constant distribution for the conditional times of seroconversion given the seroconversion windows. This allows flexible hazard shapes and also allows comparison of goodness of fit of the gamma and Weibull distributions which are often used for modelling incubation times. Computational issues are discussed. In these data, neither age at seroconversion, nor calendar time of seroconversion, nor the identification of a seroconversion illness appears to afFect incubation distributions. The Weibull distribution appears to provide a reasonable fit. The distribution of times from seroconversion to an HIV-related death is also briefly considered.     

合成孔径雷达最优量化编码器

合成孔径雷达ＳＡＲ数据率高、数据量大，对ＳＡＲ原始数据的压缩可以降低对数传和数据存储的要求。文中用ＳＢＡＳＡＰ－ＳＡＲ原始数据对合成孔径雷达信号统计模型进行了研究，提出了一种２ｂｉｔ自适应量化编码方法，并用ＳＥＡＳＡＴ—ＳＡＲ原始数据进行了编－译码实验，获得了该２ｂｉｔ量化编码器的性能指标测试结果。     

卫星气象资料广播分发差错控制技术的研究

研究了适用于卫星气象资料广播分发的三种差错控制技术方案,并用计算机进行了大量的性能模拟试验,证实了采用BCH(127,106)的方案可将误码率从10~(-3)改进为<10~(-9),传输效率为81％;卷积码的维特比(Viterbi)译码(r=1/2,k=6)方案对误码率可提供更大的改善,但传输效率<50％;收缩码方案(r=2/3,k=6)在随机差错模式下的性能甚至比预料的更好。     

Nonparametric estimation of the limiting availability

The point availability of a repairable system is the probability that the system is operating at a specified time. As time increases, the point availability converges to a positive constant called the limiting availability. Baxter and Li (1994a) developed a technique for constructing nonparametric confidence intervals for the point availability. However, nonparametric estimators of the limiting availability have not previously been studied in the literature. In this paper, we consider two separate cases: (1) the data are complete and (2) the data are subject to right censorship. For each case, a nonparametric confidence interval for the limiting availability is derived. Applications and simulation studies are presented.deceased after the paper was accepted     

THE REDUCED-RANK GROWTH CURVE MODEL FOR DISCRIMINANT ANALYSIS OF LONGITUDINAL DATA

This paper presents a method of discriminant analysis especially suited to longitudinal data. The approach is in the spirit of canonical variate analysis (CVA) and is similarly intended to reduce the dimensionality of multivariate data while retaining information about group differences. A drawback of CVA is that it does not take advantage of special structures that may be anticipated in certain types of data. For longitudinal data, it is often appropriate to specify a growth curve structure (as given, for example, in the model of Potthoff & Roy, 1964). The present paper focuses on this growth curve structure, utilizing it in a model-based approach to discriminant analysis. For this purpose the paper presents an extension of the reduced-rank regression model, referred to as the reduced-rank growth curve (RRGC) model. It estimates discriminant functions via maximum likelihood and gives a procedure for determining dimensionality. This methodology is exploratory only, and is illustrated by a well-known dataset from Grizzle & Allen (1969).