我国居民消费需求分析

近年来,我国消费率不断下降,投资率持续上升,经济增长主要依靠投资需求拉动,经济增长中的结构性矛盾日渐突出,并将影响我国经济的持续稳定健康发展。本文在分析我国居民消费需求存在的主要问题的基础上,揭示了影响我国居民消费需求扩大的基本原因,提出扩大我国居民消费需求的对策建议。     

我国法学教育实践教学的反思——兼论我国法学教育模式的选择

我国法学教育是"一站式"教学模式,注重通识教育,忽视了实践教学。西方国家多采用"两站式"、"三站式"教育模式,我国应吸取西方的教育经验,采用"两站式"的教育模式,培养适应我国社会主义市场经济需要的合格的法律人才。     

A two‐stage phase II clinical trial design with nested criteria for early stopping and efficacy

We propose a two‐stage design for a single arm clinical trial with an early stopping rule for futility. This design employs different endpoints to assess early stopping and efficacy. The early stopping rule is based on a criteria determined more quickly than that for efficacy. These separate criteria are also nested in the sense that efficacy is a special case of, but usually not identical to, the early stopping endpoint. The design readily allows for planning in terms of statistical significance, power, expected sample size, and expected duration. This method is illustrated with a phase II design comparing rates of disease progression in elderly patients treated for lung cancer to rates found using a historical control. In this example, the early stopping rule is based on the number of patients who exhibit progression‐free survival (PFS) at 2 months post treatment follow‐up. Efficacy is judged by the number of patients who have PFS at 6 months. We demonstrate our design has expected sample size and power comparable with the Simon two‐stage design but exhibits shorter expected duration under a range of useful parameter values.     

互联网对家庭消费影响效应与机理研究

基于2016年中国家庭追踪调查的数据,探究互联网使用对于家庭消费影响效应和作用机制。结果表明：互联网的使用对于家庭消费有显著的促进作用,其中互联网的购物用途对于家庭消费的促进作用最为明显,工具变量回归也证明原结论是稳健的。在作用机理的探究中,发现家庭收入是互联网使用影响家庭消费的部分中介,即互联网通过增加收入进而提升了家庭的消费水平。最后,进行分样本回归,发现在城市、东部沿海等经济发达地区中,互联网的使用促进家庭消费的效果更为明显。     

Home visiting program impacts on reducing homelessness among young mothers

In the current study, we aimed to determine the effects of Healthy Families Massachusetts (HFM), a statewide home visiting program, on young mothers’ experiences with homelessness during enrollment and after program completion. Data were drawn from a longitudinal, randomized control trial evaluation of HFM. Data collection occurred across 5 time points between 2008 and 2015 from a sample of 704 participants. The current analyses were restricted to a subsample of mothers (n?=?443) with Time 5 data (74 months post-enrollment; 59.1% program, 40.9% control), which was representative of the Time 1 sample. We used data from maternal phone interviews to assess program effects on experiences with homelessness. Young mothers who participated in HFM were less likely to experience homelessness when their children were preschool-age or older than mothers in the control group. During program participation, the number of home visits was negatively associated with concurrent homelessness when children were infants or toddlers.     

Shared journeys,linked lives: a relational-biographical approach to mobility practices

This paper innovatively extends existing practice-theoretical mobility research by examining biographical aspects of people’s everyday mobility that capture and reflect their social relations. Drawing on nine qualitative interviews with couples who live in/near Vienna without a private car, the paper demonstrates the promising potential of retrospective forms of social research for uncovering the dynamics of mobility practices across the life course. It conceptualises individuals as inherently social and mutually interconnected mobility practitioners whose complex and dynamic interactions with others make up more or less mobile households and families. The paper thus treats social relations as a major connector between the constitutive social and material elements of (mobility) practices, making an explicitly relational contribution to current practice-theoretical debates in mobility research.     

Bayesian nonparametric statistics: A new toolkit for discovery in cancer research

Many commonly used statistical methods for data analysis or clinical trial design rely on incorrect assumptions or assume an over‐simplified framework that ignores important information. Such statistical practices may lead to incorrect conclusions about treatment effects or clinical trial designs that are impractical or that do not accurately reflect the investigator's goals. Bayesian nonparametric (BNP) models and methods are a very flexible new class of statistical tools that can overcome such limitations. This is because BNP models can accurately approximate any distribution or function and can accommodate a broad range of statistical problems, including density estimation, regression, survival analysis, graphical modeling, neural networks, classification, clustering, population models, forecasting and prediction, spatiotemporal models, and causal inference. This paper describes 3 illustrative applications of BNP methods, including a randomized clinical trial to compare treatments for intraoperative air leaks after pulmonary resection, estimating survival time with different multi‐stage chemotherapy regimes for acute leukemia, and evaluating joint effects of targeted treatment and an intermediate biological outcome on progression‐free survival time in prostate cancer.     

A narrative review of interventions addressing the parental–fetal relationship

Background

Expectant parents develop varying degrees of emotional affiliation with the unborn child. Interventions supporting this relationship may be beneficial given its link to maternal health behaviour during pregnancy, as well as the parental–infant bond after birth.

Representativeness in panel surveys

ABSTRACT

A panel is a set of units recruited and used in successive surveys. When the sample unit is the household, so-called R-indicators together with the comparison of distributions of certain variables to those known in the total population help to measure the representativeness of the panel. The method is applied to Understanding Society, a U.K. household longitudinal study. At each wave, under- and over-represented groups of individuals are identified. This allows the implementation of better survey designs and procedures to reduce the bias of nonresponse.