Power imbalance and value creation in joint ventures

Joint ventures (JVs) often do not create expected value due to power imbalance between partners. Despite the fact that JV partners are embedded in relational constraints, prior research has largely relied on economic reasoning by focusing on equity ownership difference between JV partners as the main source of power imbalance. We extend prior research to also consider important relational factors represented by repeated ties between partners and network openness, as well as institutional status difference and network status difference as two additional dimensions of power imbalance. Our findings indicate that ownership power imbalance by itself does not have a significant effect on value creation. However, value creation is facilitated when there is ownership power imbalance between partners with more repeated ties. In contrast, value creation may be hindered when JV partners with unequal ownership are embedded in more open interfirm alliance networks. Furthermore, value creation is facilitated if JV partners that have unequal ownership also have network status power imbalance in the same direction.     

零膨胀计数数据的联合建模及变量选择

零膨胀计数数据破坏了泊松分布的方差-均值关系，可由取值服从泊松分布的数据和取值为零(退化分布)的数据各占一定比例所构成的混合分布所解释。本文基于自适应弹性网技术， 研究了零膨胀计数数据的联合建模及变量选择问题.对于零膨胀泊松分布，引入潜变量，构造出零膨胀泊松模型的完全似然, 其中由零膨胀部分和泊松部分两项组成.考虑到协变量可能存在共线性和稀疏性，通过对似然函数加自适应弹性网惩罚得到目标函数,然后利用EM算法得到回归系数的稀疏估计量，并用贝叶斯信息准则BIC来确定最优调节参数.本文也给出了估计量的大样本性质的理论证明和模拟研究，最后把所提出的方法应用到实际问题中。     

简论各省都督府代表联合会

武昌起义爆发后 ,各省纷纷宣布独立。为适应斗争形势的需要 ,各省代表会应运而生。与会代表在推翻清朝专制统治、建立民国的过程中表现出强烈的团结精神和合作意识 ,在制定建国原则、建立统一政府、指导南北和谈等方面作了卓越有成效的工作。各省代表会是武昌起义至中华民国建立这段历史之间一个不可忽视的环节 ,并对推动辛亥革命的深入发展起了积极作用     

Joint modeling of longitudinal data with a dependent terminal event

ABSTRACT

Longitudinal data often arise in longitudinal follow-up studies, and there may exist a dependent terminal event such as death that stops the follow-up. In this article, we propose a new joint modeling for the analysis of longitudinal data with informative observation times via a dependent terminal event and two latent variables. Estimating equations are developed for parameter estimation, and asymptotic properties of the resulting estimators are established. In addition, a generalization of the joint model with time-varying coefficients for the longitudinal response variable is considered, and goodness-of-fit methods for assessing the adequacy of the model are also provided. The proposed method works well in our simulation studies, and is applied to a data set from a bladder cancer study.     

A joint model for longitudinal data profiles and associated event risks with application to a depression study

Summary.  In many longitudinal studies, a subject's response profile is closely associated with his or her risk of experiencing a related event. Examples of such event risks include recurrence of disease, relapse, drop-out and non-compliance. When evaluating the effect of a treatment, it is sometimes of interest to consider the joint process consisting of both the response and the risk of an associated event. Motivated by a prevention of depression study among patients with malignant melanoma, we examine a joint model that incorporates the risk of discontinuation into the analysis of serial depression measures. We present a maximum likelihood estimator for the mean response and event risk vectors. We test hypotheses about functions of mean depression and withdrawal risk profiles from our joint model, predict depression from updated patient histories, characterize associations between components of the joint process and estimate the probability that a patient's depression and risk of withdrawal exceed specified levels. We illustrate the application of our joint model by using the depression data.     

Analysis of longitudinal data with drop-out: objectives, assumptions and a proposal

Summary. The problem of analysing longitudinal data that are complicated by possibly informative drop-out has received considerable attention in the statistical literature. Most researchers have concentrated on either methodology or application, but we begin this paper by arguing that more attention could be given to study objectives and to the relevant targets for inference. Next we summarize a variety of approaches that have been suggested for dealing with drop-out. A long-standing concern in this subject area is that all methods require untestable assumptions. We discuss circumstances in which we are willing to make such assumptions and we propose a new and computationally efficient modelling and analysis procedure for these situations. We assume a dynamic linear model for the expected increments of a constructed variable, under which subject-specific random effects follow a martingale process in the absence of drop-out. Informal diagnostic procedures to assess the tenability of the assumption are proposed. The paper is completed by simulations and a comparison of our method and several alternatives in the analysis of data from a trial into the treatment of schizophrenia, in which approximately 50% of recruited subjects dropped out before the final scheduled measurement time.     

长波电台和联合舰队问题没有涉及国家主权吗?——与沈志华先生商榷

上世纪50年代末期,苏联提议中苏两国共同组建长波电台和潜艇联合舰队,为了维护国家主权,中方与苏方发生了激烈的争论和斗争。最近沈志华先生根据有关资料提出长波电台和联合舰队问题没有涉及国家主权。这一观点显然是不能成立的。     

Exact inference for the two-parameter exponential distribution under Type-II hybrid censoring

Epstein (1954) introduced the Type-I hybrid censoring scheme as a mixture of Type-I and Type-II censoring schemes. Childs et al. (2003) introduced the Type-II hybrid censoring scheme as an alternative to Type-I hybrid censoring scheme, and provided the exact distribution of the maximum likelihood estimator of the mean of a one-parameter exponential distribution based on Type-II hybrid censored samples. The associated confidence interval also has been provided. The main aim of this paper is to consider a two-parameter exponential distribution, and to derive the exact distribution of the maximum likelihood estimators of the unknown parameters based on Type-II hybrid censored samples. The marginal distributions and the exact confidence intervals are also provided. The results can be used to derive the exact distribution of the maximum likelihood estimator of the percentile point, and to construct the associated confidence interval. Different methods are compared using extensive simulations and one data analysis has been performed for illustrative purposes.     

A joint latent class changepoint model to improve the prediction of time to graft failure

Summary.  The reciprocal of serum creatinine concentration, RC, is often used as a biomarker to monitor renal function. It has been observed that RC trajectories remain relatively stable after transplantation until a certain moment, when an irreversible decrease in the RC levels occurs. This decreasing trend commonly precedes failure of a graft. Two subsets of individuals can be distinguished according to their RC trajectories: a subset of individuals having stable RC levels and a subset of individuals who present an irrevocable decrease in their RC levels. To describe such data, the paper proposes a joint latent class model for longitudinal and survival data with two latent classes. RC trajectories within latent class one are modelled by an intercept-only random-effects model and RC trajectories within latent class two are modelled by a segmented random changepoint model. A Bayesian approach is used to fit this joint model to data from patients who had their first kidney transplantation in the Leiden University Medical Center between 1983 and 2002. The resulting model describes the kidney transplantation data very well and provides better predictions of the time to failure than other joint and survival models.     

国际合资企业中的合作匹配度分析

本文提出并界定了中外合资企业合作匹配度的概念,建立了合作匹配度的计算模型与合资决策模型,分析了合资协议达成的理想匹配条件。