“功能性表达性模型”与中国警察信任——基于全国样本的多重中介与调节模型分析

功能性模型认为，提升警察信任的主要方法在于预防和控制犯罪，降低犯罪率与提升公众安全感；而表达性模型认为，提升警察信任更应注重维护社会正义与社区凝聚力。基于提出促进中国警察信任度提高的理论模型，提升公众获得感、幸福感、安全感，实现国家和社会整体安全的最终目的，采用结构方程模型验证“功能性-表达性模型”与中国警察信任关系的结果表明，功能性模型与表达性模型内部因素之间存在显著路径关系，同时功能性模型显著影响表达性模型指标进而改变公众对警察的信任程度。经调节效应分析后发现，主观社会阶层负向调节被害经历到犯罪恐惧感的直接路径，社交媒体使用负向调节犯罪恐惧感到警察信任的直接路径；在主观社会阶层和社交媒体使用的共同调节作用下，“被害经历→犯罪恐惧感→警察信任”中介路径效应值，随社交媒体使用频率的提升而增大，随主观社会阶层的升高而减小。     

Genetic distance,international experience and the performance of cross-border R&D for EMNEs

Cross-border R&D can contribute to the enhancement of independent innovation capabilities of emerging markets multinational enterprises (EMNEs) by benefiting from knowledge management. However, scant research exists examining the location impact of cross-border R&D for EMNEs on performance implications. This paper fills this important theoretical gap by building upon the literature of genetic distance in connection with knowledge management. We use a panel data of Chinese high-tech listed companies to empirically examine the impact of genetic distance on the performance of cross-border R&D and the role played by international experience. Our results reveal a positive relationship between genetic distance and the performance of cross-border R&D. Importantly, we highlight the motivation for cross-border R&D of EMNEs to acquire technical knowledge magnifies the positive effects of genetic distance and performance. Furthermore, our analysis indicates that international experience significantly enhanced the positive effect of genetic distance on cross-border R&D performance. We conclude this paper by discussing theoretical contributions to genetic distance, international management and knowledge management, as well as practical implications for cross-border R&D of EMNEs.     

Regression analysis of case-cohort studies in the presence of dependent interval censoring

The case-cohort design is widely used as a means of reducing the cost in large cohort studies, especially when the disease rate is low and covariate measurements may be expensive, and has been discussed by many authors. In this paper, we discuss regression analysis of case-cohort studies that produce interval-censored failure time with dependent censoring, a situation for which there does not seem to exist an established approach. For inference, a sieve inverse probability weighting estimation procedure is developed with the use of Bernstein polynomials to approximate the unknown baseline cumulative hazard functions. The proposed estimators are shown to be consistent and the asymptotic normality of the resulting regression parameter estimators is established. A simulation study is conducted to assess the finite sample properties of the proposed approach and indicates that it works well in practical situations. The proposed method is applied to an HIV/AIDS case-cohort study that motivated this investigation.     

An additive–multiplicative mean model for panel count data with dependent observation and dropout processes

This paper discusses regression analysis of panel count data with dependent observation and dropout processes. For the problem, a general mean model is presented that can allow both additive and multiplicative effects of covariates on the underlying point process. In addition, the proportional rates model and the accelerated failure time model are employed to describe possible covariate effects on the observation process and the dropout or follow‐up process, respectively. For estimation of regression parameters, some estimating equation‐based procedures are developed and the asymptotic properties of the proposed estimators are established. In addition, a resampling approach is proposed for estimating a covariance matrix of the proposed estimator and a model checking procedure is also provided. Results from an extensive simulation study indicate that the proposed methodology works well for practical situations, and it is applied to a motivating set of real data.     

考虑消费者双重偏好的低碳供应链减排策略研究

为了削弱传统零售商在渠道博弈中的垄断地位，制造商尝试建立在线渠道与零售商展开竞争。本文在考虑消费者低碳偏好的基础上，又将消费者的渠道偏好进行区分，通过不同决策模式的对比及数值算例分析，寻求低碳供应链最优的减排边界。研究表明：1分散决策时，制造商的低碳决策会受消费者渠道偏好的影响；集中决策时，制造商的低碳决策保持不变。2不同决策模式的减排边界由渠道偏好决定，渠道偏好较大时，分散决策的减排边界更高；渠道偏好较低时，集中决策的减排边界更高；渠道偏好中立时，两者的减排边界相同。3制造商可以通过升级低碳技术、实行低碳化管理等方式降低减排成本，同时通过低碳产品认证、广告宣传等方式提高消费者对低碳产品的认可程度。     

Parenting Practices,Autonomous Motivation,and Adolescent Diet Habits

Guided by self‐determination theory, the aim of this study was to examine whether adolescents’ autonomous motivation for making healthy diet choices mediates the association between parenting practices regarding diet and adolescent food choices. We analyzed data from the NCI FLASHE study, a survey of demographically diverse parents and their adolescent children (N = 1,646 dyads). Path models supported self‐determination theory’s assertion that indirect, encouraging parenting practices fostered internal motivation; in contrast, regulation was both positively and negatively linked to motivation depending on the model. Models also yielded direct paths between parenting practices and healthy and unhealthy diet choices. Overall, regardless of what predicted motivation, adolescents’ autonomous motivation was linked with their consumption of healthier foods and drinks. As such, cultivating a sense of internal motivation during these formative years may put young people on a path toward healthy patterns of self‐regulation later in life.     

Effect of pavement and water deficit on biomass allocation and whole-tree transpiration in two contrasting urban tree species

Urban Ecosystems - Aiming to explore the species-specific responses of biomass allocation and whole-tree transpiration in urban trees to pavement and drought, a field manipulation experiment grew...     

Exploring the Effects of Conditioning Factors on the Strain–Crime Association: A Test on Incarcerated Chinese Women

A key assumption of general strain theory (GST) is that various factors condition the effects of strains on crime. Past research examining this conditioning hypothesis tended to focus on youth samples and use gender as a control variable. Using survey data from Chinese female inmates, this study tests the strain–crime relationship posited in GST as well as the hypothesized effects of the conditioning factors. Regression results show that different types of strains have distinct effects on respondents’ odds to commit violent over property crimes. Conditioning factors are found to moderate the strengths of strains toward respondents’ likelihood to commit property crimes over violent crimes.     

Estimation of the additive hazards model with interval-censored data and missing covariates

The additive hazards model is one of the most commonly used regression models in the analysis of failure time data and many methods have been developed for its inference in various situations. However, no established estimation procedure exists when there are covariates with missing values and the observed responses are interval-censored; both types of complications arise in various settings including demographic, epidemiological, financial, medical and sociological studies. To address this deficiency, we propose several inverse probability weight-based and reweighting-based estimation procedures for the situation where covariate values are missing at random. The resulting estimators of regression model parameters are shown to be consistent and asymptotically normal. The numerical results that we report from a simulation study suggest that the proposed methods work well in practical situations. An application to a childhood cancer survival study is provided. The Canadian Journal of Statistics 48: 499–517; 2020 © 2020 Statistical Society of Canada     

A class of additive transformation models for recurrent gap times

Abstract

The gap time between recurrent events is often of primary interest in many fields such as medical studies, and in this article, we discuss regression analysis of the gap times arising from a general class of additive transformation models. For the problem, we propose two estimation procedures, the modified within-cluster resampling (MWCR) method and the weighted risk-set (WRS) method, and the proposed estimators are shown to be consistent and asymptotically follow the normal distribution. In particular, the estimators have closed forms and can be easily determined, and the methods have the advantage of leaving the correlation among gap times arbitrary. A simulation study is conducted for assessing the finite sample performance of the presented methods and suggests that they work well in practical situations. Also the methods are applied to a set of real data from a chronic granulomatous disease (CGD) clinical trial.