Latent Profiles of Residential Stepfamily Relationship Quality and Family Stability

Stepfamilies are an increasingly common context in which adults and children reside. Past research has examined family processes that promote family resilience, such as dyadic relationships marked by warmth, positive communication, satisfaction, and closeness. What remains less clear is whether various profiles of dyadic relationship quality within stepfamilies exist and operate to influence stepfamily stability. Using data from the National Longitudinal Study of Adolescent to Adult Health, we conducted a latent profile analysis of mother–child, stepfather–child, and stepcouple relationship quality among a sample of 1,646 adolescents residing in married and cohabiting mother–stepfather families. Results favor a 4-profile solution, labeled high-quality, high-quality couple relationship, high-quality parent–child relationships, and low-quality. The identified latent profiles displayed differences with respect to family stability, or rates of remaining an intact family system 1 year later.     

Addressing the effect of parameter estimation on phase II monitoring of multivariate multiple linear profiles via a new cluster-based approach

Abstract

Profile monitoring is applied when the quality of a product or a process can be determined by the relationship between a response variable and one or more independent variables. In most Phase II monitoring approaches, it is assumed that the process parameters are known. However, it is obvious that this assumption is not valid in many real-world applications. In fact, the process parameters should be estimated based on the in-control Phase I samples. In this study, the effect of parameter estimation on the performance of four Phase II control charts for monitoring multivariate multiple linear profiles is evaluated. In addition, since the accuracy of the parameter estimation has a significant impact on the performance of Phase II control charts, a new cluster-based approach is developed to address this effect. Moreover, we evaluate and compare the performance of the proposed approach with a previous approach in terms of two metrics, average of average run length and its standard deviation, which are used for considering practitioner-to-practitioner variability. In this approach, it is not necessary to know the distribution of the chart statistic. Therefore, in addition to ease of use, the proposed approach can be applied to other type of profiles. The superior performance of the proposed method compared to the competing one is shown in terms of all metrics. Based on the results obtained, our method yields less bias with small-variance Phase I estimates compared to the competing approach.     

0~3岁婴幼儿父母的养育压力类型及其养育指导需求---基于潜在剖面分析的结果

为了解0~3岁婴幼儿父母的养育压力类型与养育指导需求,采用养育压力量表和养育指导需求问卷对745名婴幼儿父母进行调查。结果发现,婴幼儿父母养育压力的总体水平偏高,尤其体现在幼儿教养、外界环境、生活调适三个维度;婴幼儿父母养育压力可划分为低压力型、中压力型、高压力型三种潜在类别,中压力型父母占比最高,高压力型次之,低压力型父母占比最低;三类父母在最小子女年龄、与子女关系、居住地、主要照料人、家庭月收入、父亲学历、母亲学历变量上存在显著差异;在养育指导内容与指导形式上,三类父母既有共性需求,也有差异化需求。为缓解婴幼儿父母养育压力,建议父母自身加强养育知识学习,提前做好养育规划;家庭成员密切配合,相互支持;政府为家庭早期教养提供支持。     

An alpha-power extension for the Birnbaum–Saunders distribution

Data on fatigue to exceed a critical value (or to grow to a critical level at which failure is likely to occur) is typically adjusted using the Birnbaum–Saunders (BS) distribution [see Birnbaum ZW, Saunders SC. A new family of life distributions. J Appl Probab. 1969a;6:319–327]. Although this type of distribution is asymmetric, in some cases the degree of skewness and/or kurtosis are outside the distributional range allowed by the BS distribution. Thus, a more adequate distribution model for better adjusting such unexpected deviations is called for. With this in mind, the main object of this paper is to propose an extension of the BS distribution based on the asymmetric alpha-power family of distributions [see Pewsey A, Gómez HW, Bolfarine H. Likelihood-based inference for power distributions. Test. 2012;21(4):775–789]. This extension is called the exponentiated BS distribution. We expect that by replacing the normal distribution by such more general family, a more flexible BS family is obtained. Asymmetry in the alpha-power family is controlled by a shape parameter, which also presents a similar performance in the extended BS family. The paper presents the density function for the extended BS and derives closed-form expressions for moments. Estimation is dealt with by using maximum likelihood estimators. Large sample inference can be conducted by using the Fisher information matrix derived in the paper. Estimation performance is studied by using a small scale simulation study. Results of a real application illustrates the good performance of the proposed approach.     

Profile Monitoring Using Nonparametric Bootstrap T 2 Control Chart

In certain statistical process control applications, performance of a product or process can be monitored effectively using a linear profile or a linear relationship between a response variable and one or more explanatory variables. In this article, we design a nonparametric bootstrap control chart for monitoring simple linear profiles based on T ² statistic. We evaluate the performance of the proposed method in phase II. The average and standard deviation of the run length under different shifts in the intercept, slope, and standard deviation are considered as the performance measures. Simulation results show that the performance of the proposed bootstrap control chart improves as the size of the available data increases.     

DNA数据库:实践、困惑与进路

DNA鉴定技术在诉讼中发挥着显著的证明作用。我国自建立法庭科学DNA数据库以来, 各地数据库之规模、应用逐步扩大, 取得一定实践成效。然而, 数据库的运作也存在法律困惑:如何完善立法规范, 如何平衡强制采样与正当程序的冲突, 如何兼顾DNA信息保存与隐私权保护的目标, 如何权衡数据库推广与司法资源有限的矛盾。DNA数据库的制度完善须理性选择立法模式, 整合各地既有规范。应在《刑事诉讼法》第130条“人身检查”规定的基础上, 细化DNA采样程序;综合考虑案件性质、犯罪危害程度和有利于犯罪分子改造等因素明确入库范围;健全信息保密和救济机制, 对DNA数据库的用途、信息保存和销毁期限、违法使用DNA信息的制裁措施加以规范;此外, 还应强化质量控制与监督机制。     

A generalized semiparametric regression and its efficient estimation

We investigate a generalized semiparametric regression. Such a model can avoid the risk of wrongly choosing the base measure function. We propose a profile likelihood to efficiently estimate both parameter and nonparametric function. The main difference from the classical profile likelihood is that the profile likelihood proposed is a functional of the base measure function, instead of a function of a real variable. By making the most of the structure information of the semiparametric exponential family, we get an explicit expression of the estimator of the least favorable curve. It ensures that the new profile likelihood is computationally simple. Due to the use of the least favorable curve, the semiparametric efficiency is achieved successfully and the estimation bias is reduced significantly. Simulation studies can illustrate that our proposal is much better than the existing methodologies for most cases under study, and is robust to the different model conditions.     

Hierarchical likelihood approach for the Weibull frailty model

In this article, the proportional hazard model with Weibull frailty, which is outside the range of the exponential family, is used for analysing the right-censored longitudinal survival data. Complex multidimensional integrals are avoided by using hierarchical likelihood to estimate the regression parameters and to predict the realizations of random effects. The adjusted profile hierarchical likelihood is adopted to estimate the parameters in frailty distribution, during which the first- and second-order methods are used. The simulation studies indicate that the regression-parameter estimates in the Weibull frailty model are accurate, which is similar to the gamma frailty and lognormal frailty models. Two published data sets are used for illustration.