流动人口计划生育工作指标体系与考核评估方式初探

流动人口计划生育工作是我国计划生育工作的两大难点之一。要提高流动人口计划生育管理水平,必须建立科学的指标体系来规范流动人口计生管理。本文结合实践,论述流动人口计生管理工作指标体系设置原则,统计口径,以及管理质量考核评估方法和内容。     

Examining cross-state variation in the increase in father-only families

Each state has the power to establish its own policy and laws relating to child custody determination. The number of single-parent families with children that are headed by fathers has been growing in the United States. This paper explores the extent of cross-state variation in the prevalence in father-only families in 1990, and the extent to which there was cross-state variation in the increase in father-only families in the 1980s. The 1980 and 1990 Public Use Microdata Samples (PUMS) drawn from the US decennial censuses are used. Decomposition analyses of growth indicate that increases in the number of father-only families occurred across all states during this period, but at varying rates. The primary reason for the increase in most states is an increase in the proportion of ever-married single-parent families that are headed by a father. It is for these families that are headed by divorced or separated parents that state policy relating to child custody determination is most relevant.     

A new heteroscedastic regression to analyze mass loss of wood in civil construction in Brazil

A heteroscedastic regression based on the odd log-logistic Marshall–Olkin normal (OLLMON) distribution is defined by extending previous models. Some structural properties of this distribution are presented. The estimation of the parameters is addressed by maximum likelihood. For different parameter settings, sample sizes and some scenarios, various simulations investigate the performance of the heteroscedastic OLLMON regression. We use residual analysis to detect influential observations and to check the model assumptions. The new regression explains the mass loss of different wood species in civil construction in Brazil.     

Estimation of the parameters of symmetric stable ARMA and ARMA–GARCH models

In this article, we first propose the modified Hannan–Rissanen Method for estimating the parameters of autoregressive moving average (ARMA) process with symmetric stable noise and symmetric stable generalized autoregressive conditional heteroskedastic (GARCH) noise. Next, we propose the modified empirical characteristic function method for the estimation of GARCH parameters with symmetric stable noise. Further, we show the efficiency, accuracy and simplicity of our methods with Monte-Carlo simulation. Finally, we apply our proposed methods to model the financial data.     

家庭托育点管理实践及启示：政策工具的视角

家庭托育点的规范化对婴幼儿健康成长至关重要。通过文献收集和访谈获得既往管理举措和当前试点政策,运用政策工具进行分析和总结,探究管理家庭托育点的背景、对象和措施。结果表明：家庭托育点因经济优势而被纳入管理,现有征求意见稿管理对象偏向小规模邻托,但试点和市场偏向较大收托规模;消防审查依托既有消防验收,师资准入要求偏低,质量监管依靠政府。管理建议：应根据收托规模区分小型和大型家庭托育点开展试点;完善三方协同的管理架构,设定专门空间环境要求,提高师资准入要求,建立综合质量监管。     

'I made some mistakes . . . but I love them dearly' the views of parents of children in informal kinship care

In-depth semi-structured interviews with 30 parents of children living with relatives in informal kinship care arrangements revealed the parents' views of the reasons for the informal kinship care arrangements, quality of their relationships with the children and their caregivers, their current and future roles in their children's lives, feelings experienced when with and away from the children, positive and negative aspects of kinship care, future goals and dreams for their children, and their assessments of their own strengths and challenges. Results of these interviews suggest several implications for social work practice and research.     

ASSESSING THE RELATIONSHIP BETWEEN SYMPTOMS OF ALLERGIC RHINOCONJUNCTIVITIS AND POLLEN COUNTS

The relationship between daily pollen counts during the peak pollen season and hay fever symptoms in known sufferers of pollen allergy was investigated in a Sydney hospital‐based study. This paper develops statistical models for both the short term (day to day) associations and the longer term relationships between these time series. Possible effects of asthma status are investigated. The analyses illustrate how different relationships between time series may be explored in a simple way by working on different time scales with suitably transformed variables.     

Multiparameter evidence synthesis in epidemiology and medical decision-making: current approaches

Summary.  Alongside the development of meta-analysis as a tool for summarizing research literature, there is renewed interest in broader forms of quantitative synthesis that are aimed at combining evidence from different study designs or evidence on multiple parameters. These have been proposed under various headings: the confidence profile method, cross-design synthesis, hierarchical models and generalized evidence synthesis. Models that are used in health technology assessment are also referred to as representing a synthesis of evidence in a mathematical structure. Here we review alternative approaches to statistical evidence synthesis, and their implications for epidemiology and medical decision-making. The methods include hierarchical models, models informed by evidence on different functions of several parameters and models incorporating both of these features. The need to check for consistency of evidence when using these powerful methods is emphasized. We develop a rationale for evidence synthesis that is based on Bayesian decision modelling and expected value of information theory, which stresses not only the need for a lack of bias in estimates of treatment effects but also a lack of bias in assessments of uncertainty. The increasing reliance of governmental bodies like the UK National Institute for Clinical Excellence on complex evidence synthesis in decision modelling is discussed.     

Bayesian inference for generalized additive mixed models based on Markov random field priors

Most regression problems in practice require flexible semiparametric forms of the predictor for modelling the dependence of responses on covariates. Moreover, it is often necessary to add random effects accounting for overdispersion caused by unobserved heterogeneity or for correlation in longitudinal or spatial data. We present a unified approach for Bayesian inference via Markov chain Monte Carlo simulation in generalized additive and semiparametric mixed models. Different types of covariates, such as the usual covariates with fixed effects, metrical covariates with non-linear effects, unstructured random effects, trend and seasonal components in longitudinal data and spatial covariates, are all treated within the same general framework by assigning appropriate Markov random field priors with different forms and degrees of smoothness. We applied the approach in several case-studies and consulting cases, showing that the methods are also computationally feasible in problems with many covariates and large data sets. In this paper, we choose two typical applications.     

Recovering Information from Incremental Responses

Some yields analysed and reported in the literature have been adjusted by subtracting a control. It is found that full information can be recovered for estimable parameters and the error variance using these incremental responses, in comparison with unadjusted data. These findings are of practical importance, and they supplement materials usually found in a graduate course in linear inference. The issues are illustrated using a case study from the literature.