我国大学生创业教育问题与对策分析

在总结阐释大学生创业教育本质内涵的基础上,分析了我国大学生创业教育中存在的问题,并有针对性地提出了改进策略与建议,以期对促进我国大学生创业教育的健康发展有所启示。     

哪些创业失败者更可能卷土重来?———基于松 － 紧文化与制度环境的跨国比较研究

高失败率是创业热潮中创业者必须面对的基本事实.创业失败在为创业者带来大量情绪与财务成本的同时,也提供了独特的学习经验.如何激活创业失败者卷土重来的激情是降低创业社会成本的关键.文章整合组织学习和创业认知理论构建了统一的创业失败学习理论逻辑,结合全球创业观察(Global Entrepreneurship Monitor)、世界银行和松-紧文化3个跨国数据库,考察了不同国家文化与制度环境下不同性别个体的创业失败经历对其创业选择的影响.研究发现:与没有失败经历的个体相比,有创业失败经历的个体更可能选择创业;高宽松度的国家文化、好的制度环境分别强化了这一关系;性别与文化宽松度对这一关系有显著的三重调节效应.即在高宽松度的国家文化下,有创业失败经历的女性创业者再次创业的概率更高.将性别角色差异纳入到创业失败的分析框架中,同时也扩展了创业失败的文化与制度分析.     

社会网络、 先前经验与创业风险识别

无法识别创业风险是导致创业失败的主要原因之一,如何有效识别并管理创业风险是新创企业健康成长的关键.社会网络能够弥补创业者在识别风险过程中的信息劣势,但既有研究极少探索社会网络是否以及如何影响创业风险识别.为弥补这个研究空白,文章利用信息处理理论为研究框架,构建了创业风险识别模型.具体而言,结构洞和网络强度有利于创业者获取更多、高质量与风险相关的信息,进而识别更多的创业风险;获取信息的数量在网络强度与创业风险识别关系之间发挥完全中介作用;创业者的先前经验正向影响创业风险识别,并对结构洞与获取信息的数量之间关系起调节作用.文章讨论了研究结果的理论贡献与实践启发.     

The time‐dependent “cure‐death” model investigating two equally important endpoints simultaneously in trials treating high‐risk patients with resistant pathogens

A variety of primary endpoints are used in clinical trials treating patients with severe infectious diseases, and existing guidelines do not provide a consistent recommendation. We propose to study simultaneously two primary endpoints, cure and death, in a comprehensive multistate cure‐death model as starting point for a treatment comparison. This technique enables us to study the temporal dynamic of the patient‐relevant probability to be cured and alive. We describe and compare traditional and innovative methods suitable for a treatment comparison based on this model. Traditional analyses using risk differences focus on one prespecified timepoint only. A restricted logrank‐based test of treatment effect is sensitive to ordered categories of responses and integrates information on duration of response. The pseudo‐value regression provides a direct regression model for examination of treatment effect via difference in transition probabilities. Applied to a topical real data example and simulation scenarios, we demonstrate advantages and limitations and provide an insight into how these methods can handle different kinds of treatment imbalances. The cure‐death model provides a suitable framework to gain a better understanding of how a new treatment influences the time‐dynamic cure and death process. This might help the future planning of randomised clinical trials, sample size calculations, and data analyses.     

Involvement in the Juvenile Justice System for African American Adolescents: Examining Associations with Behavioral Health Problems

While researchers have found that African American youth experience higher levels of juvenile justice involvement at every system level (arrest, sentencing, and incarceration) relative to their other ethnic counterparts, few studies have explored how juvenile justice involvement and number of contacts might be correlated with this broad range of problems. A convenience sample of 638 African American adolescents living in predominantly low-income, urban communities participated in a survey related to juvenile justice involvement. Major findings using logistic regression models indicated that adolescents who reported juvenile justice system involvement versus no involvement were 2.3 times as likely to report mental health problems, substance abuse, and delinquent or youth offending behaviors. Additional findings documented that the higher the number of juvenile justice system contacts, the higher the rates of delinquent behaviors, alcohol and marijuana use, sex while high on drugs, and commercial sex. These findings suggest that identifying and targeting youth who have multiple juvenile justice system contacts, especially those in low-resourced communities for early intervention services, may be beneficial. Future research should examine whether peer network norms might mediate the relationships between juvenile justice involvement and youth problem behaviors.     

On pseudo-values for regression analysis in competing risks models

For regression on state and transition probabilities in multi-state models Andersen et al. (Biometrika 90:15–27, 2003) propose a technique based on jackknife pseudo-values. In this article we analyze the pseudo-values suggested for competing risks models and prove some conjectures regarding their asymptotics (Klein and Andersen, Biometrics 61:223–229, 2005). The key is a second order von Mises expansion of the Aalen-Johansen estimator which yields an appropriate representation of the pseudo-values. The method is illustrated with data from a clinical study on total joint replacement. In the application we consider for comparison the estimates obtained with the Fine and Gray approach (J Am Stat Assoc 94:496–509, 1999) and also time-dependent solutions of pseudo-value regression equations.     

Analysis of Type-II hybrid censored competing risks data

Kundu and Gupta [Analysis of hybrid life-tests in presence of competing risks. Metrica. 2007;65:159–170] provided the analysis of Type-I hybrid censored competing risks data, when the lifetime distributions of the competing cause of failures follows exponential distribution. In this paper, we consider the analysis of Type-II hybrid censored competing risks data. It is assumed that latent lifetime distributions of the competing causes of failures follow independent exponential distributions with different scale parameters. It is observed that the maximum likelihood estimators of the unknown parameters do not always exist. We propose the modified estimators of the scale parameters, which coincide with the corresponding maximum likelihood estimators when they exist, and asymptotically they are equivalent. We obtain the exact distribution of the proposed estimators. Using the exact distributions of the proposed estimators, associated confidence intervals are obtained. The asymptotic and bootstrap confidence intervals of the unknown parameters are also provided. Further, Bayesian inference of some unknown parametric functions under a very flexible Beta-Gamma prior is considered. Bayes estimators and associated credible intervals of the unknown parameters are obtained using the Monte Carlo method. Extensive Monte Carlo simulations are performed to see the effectiveness of the proposed estimators and one real data set has been analysed for the illustrative purposes. It is observed that the proposed model and the method work quite well for this data set.     

Statistical analysis of dependent competing risks model in accelerated life testing under progressively hybrid censoring using copula function

This article considers statistical analysis of dependent competing risks model from Weibull distribution in accelerated life testing, in which copula function is used to examine the dependence structure between competing failure modes. We derive the maximum likelihood estimates, the approximate, and Bootstrap confidence intervals of the parameters. The effects of different dependence structures on the estimates of parameters are investigated. The simulation is given to compare the performance of the estimates when the competing failure modes are dependent with those when the failure modes are independent. Finally, one dataset was used for illustrative purpose in conclusion.     

A general long-term aging model with different underlying activation mechanisms: Modeling,Bayesian estimation,and case influence diagnostics

In this paper we propose a general cure rate aging model. Our approach enables different underlying activation mechanisms which lead to the event of interest. The number of competing causes of the event of interest is assumed to follow a logarithmic distribution. The model is parameterized in terms of the cured fraction which is then linked to covariates. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis for the proposed model. Moreover, some discussions on the model selection to compare the fitted models are given, as well as case deletion influence diagnostics are developed for the joint posterior distribution based on the ψ-divergence, which has several divergence measures as particular cases, such as the Kullback–Leibler (K-L), J-distance, L₁ norm, and χ²-square divergence measures. Simulation studies are performed and experimental results are illustrated based on a real malignant melanoma data.     

A martingale-based test for independence of time to failure and cause of failure for competing risks models

In this article, we introduce a class of tests, using a martingale approach, for testing independence of failure time and cause of failure for competing risks data. Asymptotic distribution of the proposed test statistic is derived. The procedure is illustrated with a real-life data. A simulation study is carried out to assess the level and power of the test.