结构方程模型的特点及应用

大型工程建设项目伴随着国内经济发展而大幅增加,因而对其社会稳定风险的识别、评估及预警显得尤为迫切。有别于常规的风险识别及整体评估方法,针对关联风险因素内在关联关系的研究,有助于厘清社会稳定风险构成原理、构建预警管理体系。采用问卷调查法获取数据,经分析后构建结构方程模型（SEM）,再结合评估所得的风险因素,针对某大型机场建设项目社会稳定风险实证应用该分析方法,定量分析风险构成及大小,完善社会稳定风险评估路径。

     

论合同法组织经济的功能

民法典合同编如若增加商业特许经营合同这一新的合同类型,那么这既有利于彰显\     

我国制造业技术创新效率的实证分析—兼论与市场竞争的相关性

技术创新战略关乎中部地区能否顺利崛起,是化解我国发展“不平衡不充分”主要矛盾的关键一环。基于2000～2016年中部六省的面板数据,利用超效率DEA模型测度综合技术创新效率,基于新经济社会学的相关理论构建了影响技术创新效率的多层线性模型。结果表明：R&D经费支出和R&D人员全时当量对技术创新效率均具有明显的促进作用,但两者作用在中部六省间存在显著性差异;对中部六省的技术创新效率具有显著直接影响的因素有技术创新效率百度指数和城市化率,具有显著间接影响的有教育财政支出规模、外贸依存度、技术创新效率百度指数和工业化程度。     

Why spouses depress each other: A cross‐national study to test the shared resource hypothesis in depressive symptom concordance within older adult couples

The shared resource hypothesis suggests that married couples share the same environmental resources, which shape their health concordance. This study tests its cross‐national applicability. Cross‐sectional 2012–2013 Health and Retirement Study data from China, England, Mexico, and the United States were analyzed. Heterosexual couples (age ≥60) who were married or partnered were studied (N = 20,565 pairs). Dyadic data were analyzed by multilevel models to examine the effect of self and spousal social and physical health statuses on depressive symptoms. Regression models were used to test the relationship between couples' shared resources and depressive symptom concordance. Results indicated both husbands and wives' depressive symptoms were associated with their own and spouses' social and health statuses. Most couple‐level resources were insignificant predictors for Chinese and Mexican couples' concordance, but having more social and financial resources was associated with higher concordance among British and American couples. Self‐reported health was the most consistent predictor in all countries. The shared resource hypothesis was more applicable to depressive symptom concordance within couples in the United States and England, but not in China and Mexico. Couple‐centered intervention is suggested for clinical practice, and the spousal effect should be considered in policymaking.     

Gender,work, and childcare in Kazakhstan,Mongolia, and Russia

The current study seeks to understand the nature of gender relations within a post‐Soviet welfare model in Kazakhstan, Mongolia, and Russia. On the basis of the analysis of key labour market indicators, parental leave, and childcare policies, it finds that the welfare models in the three countries are hybrid, and neither authoritarianism in Kazakhstan and Russia nor democracy in Mongolia lead to substantive gender equality outcomes. Persistent gender inequality in these countries is underpinned by the neo‐liberal approach to welfare provision, conservative social norms, and limited agency of civil society to influence the policy agenda. Nonetheless, these states have distributed to the population with an emphasis on working mothers, and this policy choice has been driven by economic, demographic, and political considerations, which ultimately serve to support, rather than transform, the patriarchal power structure in these societies.     

中国地方政府创新模式的可持续研究 ——基于“中国政府创新最佳实践”案例（2011—2016）的QCA方法

基于2011—2016年三届“中国政府创新最佳实践”的30个案例,引入定性比较分析（QCA）,从中层理论的视角,分析了在不同条件组合的情形下,地方政府创新实践可持续案例的特点。研究发现,中国地方政府存在三种主要的创新模式及条件组合：一是试点型创新,对应条件组合为创新扩散、学术关注和上级推广;二是地方型创新,对应条件组合为未创新扩散、未学术关注和未技术创新;三是技术型创新,对应条件组合为创新扩散、学术关注和技术创新。     

The nested joint clustering via Dirichlet process mixture model

This article focuses on the clustering problem based on Dirichlet process (DP) mixtures. To model both time invariant and temporal patterns, different from other existing clustering methods, the proposed semi-parametric model is flexible in that both the common and unique patterns are taken into account simultaneously. Furthermore, by jointly clustering subjects and the associated variables, the intrinsic complex shared patterns among subjects and among variables are expected to be captured. The number of clusters and cluster assignments are directly inferred with the use of DP. Simulation studies illustrate the effectiveness of the proposed method. An application to wheal size data is discussed with an aim of identifying novel temporal patterns among allergens within subject clusters.     

Bayesian nonparametric modelling of the link function in the single-index model using a Bernstein–Dirichlet process prior

This paper proposes the use of the Bernstein–Dirichlet process prior for a new nonparametric approach to estimating the link function in the single-index model (SIM). The Bernstein–Dirichlet process prior has so far mainly been used for nonparametric density estimation. Here we modify this approach to allow for an approximation of the unknown link function. Instead of the usual Gaussian distribution, the error term is assumed to be asymmetric Laplace distributed which increases the flexibility and robustness of the SIM. To automatically identify truly active predictors, spike-and-slab priors are used for Bayesian variable selection. Posterior computations are performed via a Metropolis-Hastings-within-Gibbs sampler using a truncation-based algorithm for stick-breaking priors. We compare the efficiency of the proposed approach with well-established techniques in an extensive simulation study and illustrate its practical performance by an application to nonparametric modelling of the power consumption in a sewage treatment plant.     

Robust inference for estimating equations with nonignorably missing data based on SIR algorithm

Nonresponse is a very common phenomenon in survey sampling. Nonignorable nonresponse – that is, a response mechanism that depends on the values of the variable having nonresponse – is the most difficult type of nonresponse to handle. This article develops a robust estimation approach to estimating equations (EEs) by incorporating the modelling of nonignorably missing data, the generalized method of moments (GMM) method and the imputation of EEs via the observed data rather than the imputed missing values when some responses are subject to nonignorably missingness. Based on a particular semiparametric logistic model for nonignorable missing response, this paper proposes the modified EEs to calculate the conditional expectation under nonignorably missing data. We can apply the GMM to infer the parameters. The advantage of our method is that it replaces the non-parametric kernel-smoothing with a parametric sampling importance resampling (SIR) procedure to avoid nonparametric kernel-smoothing problems with high dimensional covariates. The proposed method is shown to be more robust than some current approaches by the simulations.     

Diagnostics of multiple group influential observations for logistic regression models

In this paper, two new multiple influential observation detection methods, GCD.GSPR and mCD*, are introduced for logistic regression. The proposed diagnostic measures are compared with the generalized difference in fits (GDFFITS) and the generalized squared difference in beta (GSDFBETA), which are multiple influential diagnostics. The simulation study is conducted with one, two and five independent variable logistic regression models. The performance of the diagnostic measures is examined for a single contaminated independent variable for each model and in the case where all the independent variables are contaminated with certain contamination rates and intensity. In addition, the performance of the diagnostic measures is compared in terms of the correct identification rate and swamping rate via a frequently referred to data set in the literature.