对转型期中国犯罪实际发案情况的估测

本文以联合国犯罪受害调查和公安部的立案不实调查为依据,对我国1978年以来犯罪的实际发案情况进行了估测。考虑到有许多犯罪案件发生后受害人没有报案以及立案不实顽症的客观存在,我国的犯罪问题实际上比以立案数为标准的统计值所反映的情况要严重得多。2004年全国犯罪发案数、犯罪率分别达到约2348万起、1800起／10万人,分别比同年犯罪立案数统计值 (471．8万起)和犯罪率统计值(363起／10万人)高4倍。不过,我国的犯罪率仍然低于世界平均水平。     

知生知死知我——"子曰:''''未知生焉知死?''''"简论

“生”与“死”是孔子学说中没有明言的问题,通过遮诠的表述,孔子表达了对“生”、“死”问题上采用对象化把握方式的反对。孔子对“知生”与“知死”割裂表诠,意在通过不可言说的言说,达到对“知生”与“知死”本是同一过程的领悟。在此领悟中,此在退回到本真能在。知生即为知死,知死即为知我。     

Models for estimating discount rates for long-term health risks using labor market data

This article utilizes evidence from job choices involving fatality risks to estimate individual discount rates for adverse health outcomes. The study compares the results from five distinct models for estimating discount rates from labor market data. The estimated discount rates range from 1% to 14% with confidence intervals that usually include financial market rates for the same period. This result, and consistent findings of significant compensating differentials for fatality risk, provide strong support for life-cycle models of individual rationality in the choice of job risks. Discounted value-of-life estimates are also developed and compared to the crosssection estimates that are more prevalent in the literature.     

Testing Target-Zone Models Using Efficient Method of Moments

The objectives of this article are threefold—(1) to test target-zone models using more efficient and direct econometric methodology than previous research, (2) to identify an implicit band, if it exists, from observed data and to test target-zone models based on the estimated implicit band rather than the stated official band, and (3) to examine whether the exchange rate can be modeled as a managed float system with a central parity that lacks a band. We find strong evidence that a model with intramarginal intervention and a narrower implicit (unofficial) band can describe the dynamics of the French franc/Deutsche mark exchange rate from January 1, 1987–July 30, 1993.     

Design priorities and disciplinary perspectives: the case of the US National Children's Study

Summary.  The National Children's Study (NCS), which was undertaken in 2000 by collaboration between several US federal government agencies, is one of the largest and boldest longitudinal studies of children's health ever undertaken. One of the key design issues has been the nature of the NCS sample. The paper describes the nature of the choices and the reasons for the decision that the NCS be based on a national probability sample. Designed as a study of the environmental influences on children's health and development, the NCS is expected to identify, enrol and follow about 100000 children from their birth to the age of 21 years. A broad definition of relevant environments of interest, and a full partnership between government, university and medical scientists, introduces considerable challenges in the design of the study.     

Morbidity measures in the presence of recurrent composite endpoints

The analysis of recurrent event data in clinical trials presents a number of difficulties. The statistician is faced with issues of event dependency, composite endpoints, unbalanced follow‐up times and informative dropout. It is not unusual, therefore, for statisticians charged with responsibility for providing reliable and valid analyses to need to derive new methods specific to the clinical indication under investigation. One method is proposed that appears to have possible advantages over those that are often used in the analysis of recurrent event data in clinical trials. Based on an approach that counts periods of time with events instead of single event counts, the proposed method makes an adjustment for patient time on study and incorporates heterogeneity by estimating an individual per‐patient risk of experiencing a morbid event. Monte Carlo simulations demonstrate that, with use of a real clinical study data, the proposed method consistently outperforms other measures of morbidity. Copyright © 2003 John Wiley & Sons, Ltd.     

Simulation study of confidence regions for canonical variate analysis

Canonical variate analysis often involves the construction of confidence regions round points representing group means in a 2-dimensional plot. Traditionally circles have always been constructed, but some authors have recently advocated ellipses as being more appropriate. This paper describes a Monte Carlo study investigating the effect of a range of factors on the inclusion rates of true population means within both types of region for normal data. The traditional circles do not perform too badly within a restricted range, but they are nearly always under-included. The ellipses usually have higher inclusion rates, and so are often closer to the nominal rate, but are sometimes over-included.     

Linking Housing Changes to Crime

Housing figures prominently in debates about crime in Britain. It has become commonplace to comment on the increasing associations between crime and council housing. This paper explores some of the issues which link housing and crime. It argues that it is important to recognize how the social base and geography of housing have changed and to understand processes which lead to an increasing concentration in council housing of those with least choice in the housing market and fewest resources elsewhere. At the same time there is a danger in overstating the associations between crime and council housing and neglecting other associations with housing, and homelessness. In view of the associations between crime and council housing, considerable effort has been expended on developing management and other responses designed to reduce crime. The general view is that a broad approach is required in such initiatives and the limited research evidence does not suggest that housing management action alone is effective in reducing crime. The association which exists between council housing and crime requires a policy response which relates to why the most deprived sections of the community are increasingly concentrated in parts of the housing market and exposed to increased risks, and one which relates to the pattern of opportunities and choices in the housing system and not just to housing management.     

ON SELECTING VARIABLES AND ASSESSING THEIR PERFORMANCE IN LINEAR DISCRIMINANT ANALYSIS

Linear discriminant analysis between two populations is considered in this paper. Error rate is reviewed as a criterion for selection of variables, and a stepwise procedure is outlined that selects variables on the basis of empirical estimates of error. Problems with assessment of the selected variables are highlighted. A leave-one-out method is proposed for estimating the true error rate of the selected variables, or alternatively of the selection procedure itself. Monte Carlo simulations, of multivariate binary as well as multivariate normal data, demonstrate the feasibility of the proposed method and indicate its much greater accuracy relative to that of other available methods.     

Regression Estimation Using Multivariate Failure Time Data and a Common Baseline Hazard Function Model

Recent ‘marginal’ methods for the regression analysis of multivariate failure time data have mostly assumed Cox (1972)model hazard functions in which the members of the cluster have distinct baseline hazard functions. In some important applications, including sibling family studies in genetic epidemiology and group randomized intervention trials, a common baseline hazard assumption is more natural. Here we consider a weighted partial likelihood score equation for the estimation of regression parameters under a common baseline hazard model, and provide corresponding asymptotic distribution theory. An extensive series of simulation studies is used to examine the adequacy of the asymptotic distributional approximations, and especially the efficiency gain due to weighting, as a function of strength of dependency within cluster, and cluster size. This revised version was published online in July 2006 with corrections to the Cover Date.