Proportional hazards models based on biased samples and estimated selection probabilities

In non‐randomized biomedical studies using the proportional hazards model, the data often constitute an unrepresentative sample of the underlying target population, which results in biased regression coefficients. The bias can be avoided by weighting included subjects by the inverse of their respective selection probabilities, as proposed by Horvitz & Thompson (1952) and extended to the proportional hazards setting for use in surveys by Binder (1992) and Lin (2000). In practice, the weights are often estimated and must be treated as such in order for the resulting inference to be accurate. The authors propose a two‐stage weighted proportional hazards model in which, at the first stage, weights are estimated through a logistic regression model fitted to a representative sample from the target population. At the second stage, a weighted Cox model is fitted to the biased sample. The authors propose estimators for the regression parameter and cumulative baseline hazard. They derive the asymptotic properties of the parameter estimators, accounting for the difference in the variance introduced by the randomness of the weights. They evaluate the accuracy of the asymptotic approximations in finite samples through simulation. They illustrate their approach in an analysis of renal transplant patients using data obtained from the Scientific Registry of Transplant Recipients     

On boosting kernel density methods for multivariate data: density estimation and classification

Statistical learning is emerging as a promising field where a number of algorithms from machine learning are interpreted as statistical methods and vice-versa. Due to good practical performance, boosting is one of the most studied machine learning techniques. We propose algorithms for multivariate density estimation and classification. They are generated by using the traditional kernel techniques as weak learners in boosting algorithms. Our algorithms take the form of multistep estimators, whose first step is a standard kernel method. Some strategies for bandwidth selection are also discussed with regard both to the standard kernel density classification problem, and to our 'boosted' kernel methods. Extensive experiments, using real and simulated data, show an encouraging practical relevance of the findings. Standard kernel methods are often outperformed by the first boosting iterations and in correspondence of several bandwidth values. In addition, the practical effectiveness of our classification algorithm is confirmed by a comparative study on two real datasets, the competitors being trees including AdaBoosting with trees.     

Hierarchical priors for Bayesian CART shrinkage

The Bayesian CART (classification and regression tree) approach proposed by Chipman, George and McCulloch (1998) entails putting a prior distribution on the set of all CART models and then using stochastic search to select a model. The main thrust of this paper is to propose a new class of hierarchical priors which enhance the potential of this Bayesian approach. These priors indicate a preference for smooth local mean structure, resulting in tree models which shrink predictions from adjacent terminal node towards each other. Past methods for tree shrinkage have searched for trees without shrinking, and applied shrinkage to the identified tree only after the search. By using hierarchical priors in the stochastic search, the proposed method searches for shrunk trees that fit well and improves the tree through shrinkage of predictions.     

清代监察官员的选任、管理及对现代监察建设的启示

清代是中国封建社会的最后阶段，中国封建社会监察制度在这一时期达到完备。作者希望通过对这一 时期监察官员选任、管理制度的探讨，对当前的监察制度建设有所借鉴。本文由两部分组成：第一部分对清代的 监察官员的选任、管理制度进行了分析；第二部分作者借鉴历史对当今的监察制度建设提出了几点建议，认为应 保持监察系统的独立性，加强监察立法，严格对监察干部的选任、管理等等。     

Estimation of the mean of the selected gamma population

Let л₁ and л₂ denote two independent gamma populations G(α₁, p) and G(α₂, p) respectively. Assume α(i=1,2)are unknown and the common shape parameter p is a known positive integer. Let Y_i denote the sample mean based on a random sample of size n from the i-th population. For selecting the population with the larger mean, we consider, the natural rule according to which the population corresponding to the larger Y_i is selected. We consider? in this paper, the estimation of M, the mean of the selected population. It is shown that the natural estimator is positively biased. We obtain the uniformly minimum variance unbiased estimator(UMVE) of M. We also consider certain subclasses of estikmators of the form c₁x₍₁₎ +c₁x₍₂₎ and derive admissible estimators in these classes. The minimazity of certain estimators of interest is investigated. Itis shown that p(p+1)^-1x₍₁₎ is minimax and dominates the UMVUE. Also UMVUE is not minimax.     

UNDERSTANDING THE IMPACT OF THE MOTHER-CHILD RELATIONSHIP ON SEX WORKERS’ DECISION TO ENTER AND LEAVE THE STREETS – LESSONS FOR SOCIAL WORK PRACTICE

This paper focuses on ‘streetwalkers’ and ‘street sex workers’ who are unlicensed sex workers not belonging to a brothel and subject to criminalization. They often face great stigmatization and are usually considered victims by service providers. Five Singaporean ex-streetwalkers (n = 5), who had left the streets for at least six months and were currently receiving or had previously received skills training at a social service agency, participated in this study. Using an agentic framework and social relational theory principles, this qualitative study explored the impact of streetwalkers’ relationship with their children on their decision to enter and leave the streets and reasons for their successful help-seeking experiences. Findings revealed them to be agents who actively used strategies to meet their goals and to sustain close relationships with their children. The mother–child relationship context was a key influence on their decision to enter and/or leave the streets. Social work practice implications include tailoring service delivery to tap into their agentic capacities and identity as mothers; research and training in provision of proactive social services in a non-judgmental manner to preserve the dignity of these women while meeting both their own and their children’s needs.     

Robust group non-convex estimations for high-dimensional partially linear models

High-dimensional data with a group structure of variables arise always in many contemporary statistical modelling problems. Heavy-tailed errors or outliers in the response often exist in these data. We consider robust group selection for partially linear models when the number of covariates can be larger than the sample size. The non-convex penalty function is applied to achieve both goals of variable selection and estimation in the linear part simultaneously, and we use polynomial splines to estimate the nonparametric component. Under regular conditions, we show that the robust estimator enjoys the oracle property. Simulation studies demonstrate the performance of the proposed method with samples of moderate size. The analysis of a real example illustrates that our method works well.     

Understanding Unique Effects of Parental Incarceration on Children: Challenges,Progress, and Recommendations

Growth in U.S. incarceration rates during the 1980s and 1990s prompted a body of research focused on understanding the diverse effects of incarceration on individuals, families, and communities. An area of particular interest has been how the incarceration of a parent may affect child well‐being. Despite what appears to be converging evidence that parental incarceration poses a significant threat to child development, this area of inquiry has yet to overcome important methodological and conceptual challenges related to selection bias. It is therefore unclear whether the difficulties that have been observed among children whose parents are incarcerated are due to the incarceration itself or to other adversities that children have experienced. The purpose of this article is to draw attention to these issues, to summarize empirical and conceptual progress in overcoming these challenges, and to suggest directions for future research.     

Public Sexual Cultures: A Systematic Review of Qualitative Research Investigating Men's Sexual Behaviors with Men in Public Spaces

Resurgent HIV and sexually transmitted infection incidence among men who have sex with men (MSM) requires an urgent re-examination of sexual transmission sites. To these ends, we systematically review qualitative literature concerning men's sexual behaviors within public sex environments (PSEs). Sex, therein, is negotiated by the highly codified, largely nonverbal practice of “cruising.” A generic, shared PSE sexual culture emerges from the literature—across locations, countries, and decades—because of the importance of concealment and common structural constraints on sexual encounters in PSEs. However, differences in local geography and facilities may transform key features of this, resulting in specific, local sexual cultures emerging for each locale. We argue that, although sexual cultures developed to minimize nonsexual cruising risks, they may be exploited to improve contemporary in situ outreach work.     

论蒙古族聚居区县域经济发展的路径选择——以阿鲁科尔沁旗为例

以阿鲁科尔沁旗为例，分析蒙古族聚居区县域经济基本特征；从生态环境、基础设施条件、资金及教育等方面入手，阐述制约蒙古族聚居区县域经济发展的主要因素；提出蒙古族聚居区县域经济发展的路径选择，打造蒙古族聚居区县城经济发展的基础。