Improved inference for a linear mixed-effects model when the subpopulation effects are clustered

We provide Bayesian methodology to relax the assumption that all subpopulation effects in a linear mixed-effects model have, after adjustment for covariates, a common mean. We expand the model specification by assuming that the m subpopulation effects are allowed to cluster into d groups where the value of d, 1?d?m, and the composition of the d groups are unknown, a priori. Specifically, for each partition of the m effects into d groups we only assume that the subpopulation effects in each group are exchangeable and are independent across the groups. We show that failure to take account of this clustering, as with the customary method, will lead to serious errors in inference about the variances and subpopulation effects, but the proposed, expanded, model leads to appropriate inferences. The efficacy of the proposed method is evaluated by contrasting it with both the customary method and use of a Dirichlet process prior. We use data from small area estimation to illustrate our method.     

Posterior consistency of random effects models for binary data

In longitudinal studies or clustered designs, observations for each subject or cluster are dependent and exhibit intra-correlation. To account for this dependency, we consider Bayesian analysis for conditionally specified models, so-called generalized linear mixed model. In nonlinear mixed models, the maximum likelihood estimator of the regression coefficients is typically a function of the distribution of random effects, and so the misspecified choice of the distribution of random effects can cause bias in the estimator. To avoid the problem of the misspecification of the distribution of random effects, one can resort in nonparametric approaches. We give sufficient conditions for posterior consistency of the distribution of random effects as well as regression coefficients.     

基于Gibbs抽样算法的面板数据分位回归方法

 文章讨论了含有随机效应的面板数据模型,利用非对称Laplace分布与分位回归之间的关系,文章建立了一种贝叶斯分层分位回归模型。通过对非对称Laplace分布的分解,文章给出了Gibbs抽样算法下模型参数的点估计及区间估计,模拟结果显示,在处理含随机效应的面板数据模型中,特别是在误差非正态的情况下,本文的方法优于传统的均值模型方法。文章最后利用新方法对我国各地区经济与就业面板数据进行了实证研究,得到了有利于宏观调控的有用信息。     

Near-Balanced Incomplete Block Designs,With an Application to Poster Competitions

Judging scholarly posters creates a challenge to assign the judges efficiently. If there are many posters and few reviews per judge, the commonly used balanced incomplete block design is not a feasible option. An additional challenge is an unknown number of judges before the event. We propose two connected near-balanced incomplete block designs that both satisfy the requirements of our setting: one that generates a connected assignment and balances the treatments and another one that further balances pairs of treatments. We describe both fixed and random effects models to estimate the population marginal means of the poster scores and rationalize the use of the random effects model. We evaluate the estimation accuracy and efficiency, especially the winning chance of the truly best posters, of the two designs in comparison with a random assignment via simulation studies. The two proposed designs both demonstrate accuracy and efficiency gain over the random assignment.     

考虑退货影响的品牌商O2O渠道选择与决策优化

考虑网购顾客退货影响,利用消费者效用理论分别构建了网络、实体及O2O渠道不同混合模式下的需求函数,研究了品牌商在单一网络渠道、"网络+O2O"渠道、"网络+实体"以及"网络+O2O+实体"渠道模式下的最优定价策略,分析了网络渠道退货率对不同渠道组合下品牌商最优定价与利润的影响,着重讨论了网络品牌商和"网络+实体"双渠道品牌商选择O2O渠道的条件。研究表明,较高的网络渠道退货率将导致较高的网络渠道定价,降低品牌商利润。若开设O2O渠道不能降低网络渠道退货率,品牌商选择O2O渠道取决于其运营成本及退货率大小,运营成本低且销售个性化等高退货率产品的品牌商适合开设O2O渠道;若开设O2O渠道可以降低网络渠道退货率,品牌商是否开设O2O渠道取决于运营成本、退货率以及运费。或运营成本低,或运营成本高但运费低,或运营成本高、运费高以及销售高退货率产品,这三种情形下的品牌商应该选择开设O2O渠道。     

Testing for coefficient stability of AR(1) model when the null is an integrated or a stationary process

In this paper, we propose a new test for coefficient stability of an AR(1) model against the random coefficient autoregressive model of order 1 neither assuming a stationary nor a non-stationary process under the null hypothesis of a constant coefficient. The proposed test is obtained as a modification of the locally best invariant (LBI) test by Lee [(1998). Coefficient constancy test in a random coefficient autoregressive model. J. Statist. Plann. Inference 74, 93–101]. We examine finite sample properties of the proposed test by Monte Carlo experiments comparing with other existing tests, in particular, the LBI test by McCabe and Tremayne [(1995). Testing a time series for difference stationary. Ann. Statist. 23 (3), 1015–1028], which is for the null of a unit root process against the alternative of a stochastic unit root process.     

从生态个体维度解析道德效用的伦理思想

从生态个体的维度探究道德效用,旨在确认道德对个体生存、自由与幸福的效用,引导行为主体自发地进行道德实践。首先基于道德效用相关概念的微观分析,道德效用包含着道德行为使受益者受益的思想内涵。其次从生存、自由与幸福这三个生态个体逐步递进的追求展开对道德效用的探微,具体表现为道德效用是利他的,意味着道德主体的行为使他人成为获益者,随着道德效用在时间与空间层面的推演发展,回馈效应又会使道德主体自身受益,最终演化为道德效用也是利己的,这是道德共同体的有效构建。最后站在新时代公民道德建设这一新的历史起点上,道德效用的社会生态蕴意突显了生态个体与社会生态系统和谐共存的伦理智慧,其注重以人为本、利他与利己均衡发展以及培育公共品格的伦理思想可以提升伦理道德体系话语的亲和力和感召力,使道德主体选择正确的行为方式去把握生态个体之间的关系。     

Bad luck vs. self-inflicted neediness – An experimental investigation of gift giving in a solidarity game

We experimentally examine the impact of self-inflicted neediness on the solidarity behavior of subjects. In one treatment in our solidarity experiment all subjects face the same probability of becoming needy, in the other treatment subjects have the choice between a secure payment and a lottery which includes a certain probability of becoming needy. Then all subjects are asked how much they will give to losers in their group to investigate if people are willing to give the same gifts whether or not subjects are responsible for inequality in payoffs. We found evidence for allocative as well as for procedural utility concerns.     

开征环境税对经济增长影响的实证研究——基于十二个发达国家二氧化碳税开征经验的面板数据分析

本文利用芬兰等十二个已开征二氧化碳税的发达国家1980～2009年间的跨国面板数据进行随机效应估计.结果发现:开征环境税在短期内可能给经济增长带来负向冲击;但环境税对经济增长的影响更多地体现为长期冲击,且这种长期冲击是显著的负向影响.因此,开征环境税时,不仅要通过税收体系调整缓解企业成本上升在短期内给经济增长带来的不利冲击,更应从长期影响的视角出发,设计配套政策,降低环境税在长期内对经济增长和社会福利可能存在的不利影响.     

The Diagnostic Utility of the Child Sexual Behavior Inventory for Sexual Abuse: A Systematic Review

Children with alleged child sexual abuse (CSA) need to be assessed systematically. The use of validated instruments during the assessment, like the Child Sexual Behavior Inventory (CSBI), could add diagnostic value. We aim to assess the diagnostic utility of the CSBI to differentiate between sexually abused and non-abused children. We conducted a systematic review. We searched the electronic databases MEDLINE and PsychInfo for studies comparing CSBI scores in sexually abused children and non-abused children (2–12 years old). Two independent reviewers extracted data and assessed the methodological quality. We included 7 (out of 1048) articles. The CSBI total scores were significantly higher in CSA-victims compared with non-abused children (in case–control settings). However, in children with suspected CSA, the results were ambiguous. One study reported significant differences. Another study reported weak diagnostic ability for the CSBI-3 in children with suspected CSA (a sensitivity and specificity of 0.50, with a positive predictive value of 0.28, and a negative predictive value of 0.72). Research on the diagnostic utility of the CSBI for suspected CSA is limited and shows disappointing results. Until more research is done, the CSBI should not be used on its own to differentiate between sexually abused and non-abused children.