Understanding Estimators of Treatment Effects in Regression Discontinuity Designs

In this paper, we propose two new estimators of treatment effects in regression discontinuity designs. These estimators can aid understanding of the existing estimators such as the local polynomial estimator and the partially linear estimator. The first estimator is the partially polynomial estimator which extends the partially linear estimator by further incorporating derivative differences of the conditional mean of the outcome on the two sides of the discontinuity point. This estimator is related to the local polynomial estimator by a relocalization effect. Unlike the partially linear estimator, this estimator can achieve the optimal rate of convergence even under broader regularity conditions. The second estimator is an instrumental variable estimator in the fuzzy design. This estimator will reduce to the local polynomial estimator if higher order endogeneities are neglected. We study the asymptotic properties of these two estimators and conduct simulation studies to confirm the theoretical analysis.     

A Seemingly Unrelated Nonparametric Additive Model with Autoregressive Errors

This article considers a nonparametric additive seemingly unrelated regression model with autoregressive errors, and develops estimation and inference procedures for this model. Our proposed method first estimates the unknown functions by combining polynomial spline series approximations with least squares, and then uses the fitted residuals together with the smoothly clipped absolute deviation (SCAD) penalty to identify the error structure and estimate the unknown autoregressive coefficients. Based on the polynomial spline series estimator and the fitted error structure, a two-stage local polynomial improved estimator for the unknown functions of the mean is further developed. Our procedure applies a prewhitening transformation of the dependent variable, and also takes into account the contemporaneous correlations across equations. We show that the resulting estimator possesses an oracle property, and is asymptotically more efficient than estimators that neglect the autocorrelation and/or contemporaneous correlations of errors. We investigate the small sample properties of the proposed procedure in a simulation study.     

Computing the log concave NPMLE for interval censored data

In analyzing interval censored data, a non-parametric estimator is often desired due to difficulties in assessing model fits. Because of this, the non-parametric maximum likelihood estimator (NPMLE) is often the default estimator. However, the estimates for values of interest of the survival function, such as the quantiles, have very large standard errors due to the jagged form of the estimator. By forcing the estimator to be constrained to the class of log concave functions, the estimator is ensured to have a smooth survival estimate which has much better operating characteristics than the unconstrained NPMLE, without needing to specify a parametric family or smoothing parameter. In this paper, we first prove that the likelihood can be maximized under a finite set of parameters under mild conditions, although the log likelihood function is not strictly concave. We then present an efficient algorithm for computing a local maximum of the likelihood function. Using our fast new algorithm, we present evidence from simulated current status data suggesting that the rate of convergence of the log-concave estimator is faster (between \(n^{2/5}\) and \(n^{1/2}\)) than the unconstrained NPMLE (between \(n^{1/3}\) and \(n^{1/2}\)).     

Power analysis for clustered non-continuous responses in multicenter trials

Power analysis for multi-center randomized control trials is quite difficult to perform for non-continuous responses when site differences are modeled by random effects using the generalized linear mixed-effects model (GLMM). First, it is not possible to construct power functions analytically, because of the extreme complexity of the sampling distribution of parameter estimates. Second, Monte Carlo (MC) simulation, a popular option for estimating power for complex models, does not work within the current context because of a lack of methods and software packages that would provide reliable estimates for fitting such GLMMs. For example, even statistical packages from software giants like SAS do not provide reliable estimates at the time of writing. Another major limitation of MC simulation is the lengthy running time, especially for complex models such as GLMM, especially when estimating power for multiple scenarios of interest. We present a new approach to address such limitations. The proposed approach defines a marginal model to approximate the GLMM and estimates power without relying on MC simulation. The approach is illustrated with both real and simulated data, with the simulation study demonstrating good performance of the method.     

行业协会对行政权力制约的缺乏及对策

任何公权力都需要监督和制约,行政权力尤为如此.行业协会不同于一般的社会组织,它的出现是对传统国家管理的修正,是社会发展的必然,是对行政权力进行制约的有效武器.但是,我国行业协会的发展却不尽如人意.文章从我国行业协会的历史和现状两方面分析了我国目前行业协会对行政权力缺乏制约的原因,并提出了相关解决的对策.     

大学生“郁闷”心态的成因及克服对策

"郁闷"心态是折射大学生心理的一面镜子。对大学生郁闷心态的意义表征、形成原因及克服对策进行全方位、多角度的理性分析,有利于大学生生活世界的构建和身心的健康发展。     

试论芭蕉的俳谐之旅与风雅之道

在日本文学史上"风雅"一般指全体艺术,而贯穿在松尾芭蕉艺术之道的"风雅"为俳谐之意.松尾芭蕉把乾坤之变视为风雅之因,在天地自然变化之中一味追求新的俳风,直逼以"诚"为本的风雅之道.当时松尾芭蕉接受中国文化时的审美心理的调整过程,以及创造新质的选择机制,从他的旅行记中得到了阐释.     

特征AHP在高校教师教学质量评定中的应用

本文针对高校教师教学质量的评定提出了一种特征层次分析法。首先通过分析教学质量的影响因素,建立三层层次分析模型。在其基础上引入特征法,选取特征群并确定特征群中个体的权重,利用反算法根据组合权重及方案层权重,求取准则层评定指标权重,避免了不同质指标间对比的不确定性,摒除了专家直接给出评定指标对比矩阵的主观性,减少了对教师评定过程的不一致性和不完备性。     

论语言性别差异与社会文化的互构

社会文化在人们的实践活动中建构语言性别差异,同时语言性别差异诱导和暗示社会文化的变化和发展,语言性别差异和社会文化处于互构的关系中.在语言性别差异和社会文化的互构关系中,后者的作用具有决定和主导的作用,不能夸大前者对后者的建构影响.     

Opportunities for woman-initiated HIV prevention methods among female sex workers in southern China

Rapid changes in China over the past two decades have led to significant problems associated with population migration and changing social attitudes, including a growing sex industry and concurrent increases in STIs and HIV. This article reports results of an exploratory study of microbicide acceptability and readiness and current HIV prevention efforts among female sex workers in two rural and one urban town in Hainan and Guangxi Provinces in southern China. The study focused on these women's knowledge and cultural understandings of options for protecting themselves from exposure to STIs and HIV, and the potential viability and acceptability of woman-initiated prevention methods. We report on ethnographic elicitation interviews conducted with women working within informal sex-work establishments (hotels, massage and beauty parlors, roadside restaurants, boarding houses). We discuss implications of these findings for further promotion of woman-initiated prevention methods such as microbicides and female condoms among female sex workers in China.