Bayesian analysis of the difference of two proportions

In this article we give the expression of the prior distribution of p₁-P₂, where P₁ and P₂ and independent proportions with a beta prior each. The expression derived for the posterior distribution of P₁-P₂ then shows the closure of the beta-difference family for independent dual Bernoulli samples. Other bayesian results are also presented.     

Bayesian robustness of credible regions in the presence of nuisance parameters

The problem of finding the most robust γ-level credible region for the parameter of interest in the presence of a nuisance parameter, with respect to a class of ε-contaminated priors, is studied. The case of arbitrary con-taminations is first analyzed; it is proved that the most robust region for the parameter of interest is theγ-level highest marginal likelihood region (forγ ≥ 0.5). Then, the result is extended to any measurable (not necessarily one-to-one) function of the parameter. Finally, the case of contaminations assigning fixed probabilities to the sets of a partition of the parameter space is analyzed and a partial result is given.     

A bayesian method in determining the order of a finite state markov chain

In this paper, we use the Bayesian method in the application of hypothesis testing and model selection to determine the order of a Markov chain. The criteria used are based on Bayes factors with noninformative priors. Com¬parisons with the commonly used AIC and BIC criteria are made through an example and computer simulations. The results show that the proposed method is better than the AIC and BIC criteria, especially for Markov chains with higher orders and larger state spaces.     

A Monte Carlo simulation study of two-sided tolerance intervals in balanced one-way random effects model for non-normal errors

Recently, Ong and Mukerjee [Probability matching priors for two-sided tolerance intervals in balanced one-way and two-way nested random effects models. Statistics. 2011;45:403–411] developed two-sided Bayesian tolerance intervals, with approximate frequentist validity, for a future observation in balanced one-way and two-way nested random effects models. These were obtained using probability matching priors (PMP). On the other hand, Krishnamoorthy and Lian [Closed-form approximate tolerance intervals for some general linear models and comparison studies. J Stat Comput Simul. 2012;82:547–563] studied closed-form approximate tolerance intervals by the modified large-sample (MLS) approach. We compare the performances of these two approaches for normal as well as non-normal error distributions. Monte Carlo simulation methods are used to evaluate the resulting tolerance intervals with regard to achieved confidence levels and expected widths. It turns out that PMP tolerance intervals are less conservative for data with large number of classes and small number of observations per class and the MLS procedure is preferable for smaller sample sizes.     

Intrinsic Bayesian inference on a Poisson rate and on the ratio of two Poisson rates

Our purpose is to explore the intrinsic Bayesian inference on the rate of a Poisson distribution and on the ratio of the rates of two independent Poisson distributions, with the natural conjugate family of priors in the first case and the semi-conjugate family of priors defined by Laurent and Legrand (2011) in the second case. Intrinsic Bayesian inference is derived from the Bayesian decision theory framework based on the intrinsic discrepancy loss function. We cover in particular the case of some objective Bayesian procedures suggested by Bernardo when considering reference priors.     

Marginal and Conditional Distribution Estimation from Double‐sampled Semi‐competing Risks Data

Informative dropout is a vexing problem for any biomedical study. Most existing statistical methods attempt to correct estimation bias related to this phenomenon by specifying unverifiable assumptions about the dropout mechanism. We consider a cohort study in Africa that uses an outreach programme to ascertain the vital status for dropout subjects. These data can be used to identify a number of relevant distributions. However, as only a subset of dropout subjects were followed, vital status ascertainment was incomplete. We use semi‐competing risk methods as our analysis framework to address this specific case where the terminal event is incompletely ascertained and consider various procedures for estimating the marginal distribution of dropout and the marginal and conditional distributions of survival. We also consider model selection and estimation efficiency in our setting. Performance of the proposed methods is demonstrated via simulations, asymptotic study and analysis of the study data.     

A Note on Priors for the Multinomial Model

An “overall objective” prior proposed for the multinomial model is shown to be inadequate in the presence of zero counts. An earlier proposed reference prior for when interest is in a particular category suffers from similar problems. It is argued that there is no need to deviate from the uniform prior proposed by Jeffreys, for which links with a non-Bayesian approach, when prediction is of interest, are shown.     

高校图书馆与大学生素质教育刍议

素质教育和高校图书馆是一个相互依存、相互促进、共同发展的统一体，高校图书馆在素质教育中发挥了主观引导和客观影响的作用。过去的应试教育给高校图书馆建设带来了一些负面影响，高校图书馆要应对素质教育理念的挑战与要求就必须加强自身信息化建设、加强用户教育、强化育人功能并提高自身化内涵。     

Random coefficient models for binary longitudinal responses with attrition

We extend the approach introduced by Aitkin and Alfò (1998, Statistics and Computing, 4, pp. 289–307) to the general framework of random coefficient models and propose a class of conditional models to deal with binary longitudinal responses, including unknown sources of heterogeneity in the regression parameters as well as serial dependence of Markovian form.Furthermore, we discuss the extension of the proposed approach to the analysis of informative drop-outs, which represent a central problem in longitudinal studies, and define, as suggested by Follmann and Wu (1995, Biometrics, 51, pp. 151–168), a conditional specification of the full shared parameter model for the primary response and the missingness indicator. The model is applied to a dataset from a methadone maintenance treatment programme held in Sydney in 1986 and previously analysed by Chan et al. (1998, Australian & New Zealand Journal of Statistics, 40, pp. 1–10).All of the proposed models are estimated by means of an EM algorithm for nonparametric maximum likelihood, without assuming any specific parametric distribution for the random coefficients and for the drop-out process.A small scale simulation work is described to explore the behaviour of the extended approach in a number of different situations where informative drop-outs are present.     

我国危机事件下从众意向模型——基于FISHBEIN合理行为模型的修正研究

在合理行为模型的基础上建立我国的危机事件从众行为意向模型,并应用该模型对2类典型危机事件下的从众行为进行问卷调查和实证分析。在合理行为模型的基础上添加了信息性社会影响因变量,并根据已有研究在变量之间增加了新的联系。以未知性的流感病毒传播和水灾捐助为例,通过实证研究对模型进行了修正,使其具有很好的解释能力。实证结果表明,危机事件下自我救助性从众行为中信息性社会影响将占据主导作用,而在助他性从众行为中规范性社会影响占据主导作用,在2种不同的从众行为中,信息性社会影响与规范性社会影响的作用方式也表现迥异。