On the Breslow–Holubkov estimator

Breslow and Holubkov (J Roy Stat Soc B 59:447–461 1997a) developed semiparametric maximum likelihood estimation for two-phase studies with a case–control first phase under a logistic regression model and noted that, apart for the overall intercept term, it was the same as the semiparametric estimator for two-phase studies with a prospective first phase developed in Scott and Wild (Biometrica 84:57–71 1997). In this paper we extend the Breslow–Holubkov result to general binary regression models and show that it has a very simple relationship with its prospective first-phase counterpart. We also explore why the design of the first phase only affects the intercept of a logistic model, simplify the calculation of standard errors, establish the semiparametric efficiency of the Breslow–Holubkov estimator and derive its asymptotic distribution in the general case.     

Thinking possibilistically in a probabilistic world

We cannot live on the knife edge of disaster all the time. We cannot even think about disastrous extremes with any clarity, says Lee Clarke . For 300 years we have equated thinking probabilistically with thinking rationally, but is that enough for thinking about terrorism, air crashes—or even God?     

Generalized inferences on the common mean vector of several multivariate normal populations

The hypothesis testing and confidence region are considered for the common mean vector of several multivariate normal populations when the covariance matrices are unknown and possibly unequal. A generalized confidence region is derived using the concepts of generalized method based on the generalized p$p$-value. The generalized confidence region is illustrated with two numerical examples. The merits of the proposed method are numerically compared with those of existing methods with respect to their expected area or expected d-dimensional volumes and coverage probabilities under different scenarios.     

The robustness of the quasilikelihood estimator

The quasilikelihood estimator is widely used in data analysis where a likelihood is not available. We illustrate that with a given variance function it is not only conservative, in minimizing a maximum risk, but also robust against a possible misspecification of either the likelihood or cumulants of the model. In examples it is compared with estimators based on maximum likelihood and quadratic estimating functions.     

Assessment of influence in non-linear measurement error models

We consider the assessment of outliers and influential observation in non-linear measurement error models. Residuals, leverage measures and case-deletiondiagonostics are examined. The method of local influence is also applied to the models. In particular, the perturbation of measurement error variances has been found useful in assessing the adequancy of the model assumptions. A numerical example is given to illustrate the application of the diagonostics.     

渐进式与休克疗法式改革的比较分析

我国选择了渐进市场化的改革道路,这是一条有别于西方市场经济理论的改革道路,尽管在实践上取得了巨大的成就,但在理论上却备受争议。本文试图通过理论的角度,分析说明渐进式改革从总体上优于休克疗法式的改革,并指出,在渐进式改革的过程中,只单方面进行体制内或体制外的改革,效果都是一样的,并且是渐进式改革模式中效率最差的。而同时进行体制内和体制外的市场化改革是最优的渐进改革模式。     

Developing From Tranditional Microscale Chemistry to Microscale Green Chemistry

Microscale chemistry is appealing to all levels of education.In contrast to conventional macroscale chemistry,only minute amount of chemicals are required to undertaking a chemical investigation.     

Relationships between Economics,Welfare, Social Network Factors,and Net Migration in the United States

By using economics, welfare and social network factors as frames of reference, this study aims to explore the relationship between these three factors and net migration to various US states. Adopting related variables collected from official aggregate data, this study first utilizes Logit Regression analysis to draw out seven variables that best explain net migration to the various states, then employs these variables in LISREL analyses to build a model explaining the factors influencing net migration to the various US states. Concretely, this research obtained the following findings: (1) the seven variables ‐‐ the average rate of net migrants of 2002–2005, Medicaid, federal aid, employment rate, non‐poverty population rate, and SSI subsidy ‐‐ all significantly affected (p < 0.01 or p < 0.05) net migration in 2006; (2) the main influences on net migration for the various states are, from highest to lowest, social network, economic, and welfare factors. More specifically, a better explanation is that, through the social network factor, economic and welfare factors exert an increased influence on the net number of migrants; and (3) as for the influence of social network factors on the number of net migrants, the social network factor for the previous year was found to best explain domestic migration flows, while the social network factor for the previous three‐to‐four years best explained international migration flows.