The k-sample problem in a multi-state model and testing transition probability matrices

The choice of multi-state models is natural in analysis of survival data, e.g., when the subjects in a study pass through different states like ‘healthy’, ‘in a state of remission’, ‘relapse’ or ‘dead’ in a health related quality of life study. Competing risks is another common instance of the use of multi-state models. Statistical inference for such event history data can be carried out by assuming a stochastic process model. Under such a setting, comparison of the event history data generated by two different treatments calls for testing equality of the corresponding transition probability matrices. The present paper proposes solution to this class of problems by assuming a non-homogeneous Markov process to describe the transitions among the health states. A class of test statistics are derived for comparison of \(k\) treatments by using a ‘weight process’. This class, in particular, yields generalisations of the log-rank, Gehan, Peto–Peto and Harrington–Fleming tests. For an intrinsic comparison of the treatments, the ‘leave-one-out’ jackknife method is employed for identifying influential observations. The proposed methods are then used to develop the Kolmogorov–Smirnov type supremum tests corresponding to the various extended tests. To demonstrate the usefulness of the test procedures developed, a simulation study was carried out and an application to the Trial V data provided by International Breast Cancer Study Group is discussed.     

Using expected values to simplify decision making under uncertainty

A simulation study examines the impact of a simplification strategy that replaces distributional attribute evaluations with their expected values and uses those expectations in an additive value model. Several alternate simplified forms and approximation approaches are investigated, with results showing that in general the simplified models are able to provide acceptable performance that is fairly robust to a variety of internal and external environmental changes, including changes to the distributional forms of the attribute evaluations, errors in the assessment of the expected values, and problem size. Certain of the simplified models are shown to be highly sensitive to the form of the underlying preference functions, and in particular to extreme non-linearity in these preferences.     

美国极权主义心理解析——以《裸者与死者》为例

《裸者与死者》对美国极权主义的揭露与批判是批评界研究的焦点。新精神分析学派认为,极权主义和法西斯主义拥有同样的心理基础"权威主义性格",其运行的心理机制取决于施虐-受虐冲动,为剖析小说中复杂、矛盾的集体性格特征,揭示美国军队"机器人"的产生缘由提供了理论依据。以《裸者与死者》为例对极权主义的心理解析有助于挖掘现代战争与杀戮的深层根源,对当下有警示作用。     

The influence of organizational identification on organizational knowledge management (KM)

Information technology (IT) outsourcing vendor organizations contain isolated business units whose creation and sustenance greatly facilitate business operations. But they also introduce important challenges for organizational knowledge management (KM). In this paper, based on 7 months of intensive field-work at India Inc., a leading Indian IT firm, we looked at how members’ identification with two organizations, their own and their client organization, influences their compliance with an organizational KM initiative. The findings show that members have difficulties in complying with the expectations of the organizational KM initiative owing to a stronger identification with their client organizations. At the same time, they comply readily with KM initiatives at the business unit level. The findings show that KM managers at India Inc. use the help of middle level managers in the business units in their efforts to improve members’ compliance with organizational KM. Theoretical and managerial implications of the study are discussed.     

An introduction to copula-based bivariate reliability Concepts

Several attempts were made in the literature to generalize the notions based on univariate quantiles to higher dimensions. As quantile-based reliability concepts are receiving much attention, it is important to address these problems in the field of Reliability theory. In this paper, bivariate reliability concepts using the dependence structure are introduced. The properties and characterizations of the bivariate reliability concepts are presented; it includes the characterization based on the relationship between bivariate hazard rate and bivariate mean residual life. The bivariate reliability concepts in reversed time are also studied.     

On the mixtures of Weibull and Pareto (IV) distribution: An alternative to Pareto distribution

Finite mixture models have provided a reasonable tool to model various types of observed phenomena, specially those which are random in nature. In this article, a finite mixture of Weibull and Pareto (IV) distribution is considered and studied. Some structural properties of the resulting model are discussed including estimation of the model parameters via expectation maximization (EM) algorithm. A real-life data application exhibits the fact that in certain situations, this mixture model might be a better alternative than the rival popular models.     

Some estimation procedures of sensitive character using scrambled response techniques in successive sampling

This paper is an attempt to analyze the effect of scrambled response techniques to estimate the current population mean in two-occasion successive sampling when study and auxiliary variables are sensitive in nature. Using additive and multiplicative scrambled response models on both occasions, some generalized estimation strategies of current population mean have been proposed and their properties are examined. Empirical studies are performed on real data (abortion rate in the states of United States) and simulation studies are also carried out to evaluate the performances of the proposed estimators over other estimators. Results have proved the worthiness of the scrambled response techniques in real-life situations.     

Distributions of statistics describing concentration of runs in non homogeneous Markov-dependent trials

In the first n, n ? 3, trials of a non homogeneous zero-one Markov chain of first order, we consider runs of ones of length exceeding a threshold. The article deals with statistics denoting, the length and the position of the shortest segment of the chain in which all such runs of ones are concentrated. The study provides recursive schemes for conditional distributions of these statistics. Numerical examples illustrate the theoretical results.