Factors associated with a positive childbirth experience in Brazilian women: A cross-sectional study

BackgroundHaving a positive childbirth experience is an increasingly valued outcome. Few studies evaluated the women’s satisfaction with childbirth through face-to-face interviews out of the health service environment. The objective of this study was to identify factors associated with a higher level of satisfaction with the childbirth experience among Brazilian women.MethodsThis cross-sectional study involved 287 women giving birth in two hospitals in southern Brazil. Women who gave birth to healthy newborns at term were randomly selected. Face-to-face interviews were conducted 31–37 days after delivery, at the mothers’ homes, using a structured questionnaire. Satisfaction with the childbirth experience was measured using a Likert-type scale ranging from very satisfied to very dissatisfied. Prevalence ratios (PR) were estimated using Poisson regression with robust variance.ResultsFollowing hierarchical multivariate analysis, the following factors remained associated with a higher level of satisfaction with the childbirth experience: being satisfied with antenatal care (PR = 1.30; 95% confidence interval [95%CI] = 1.06−1.59), understanding the information provided by health professionals during labor and delivery (PR = 1.40; 95%CI = 1.01−1.95), not having reported disrespect and abuse (PR = 1.53; 95%CI = 1.01−2.31), and having had the baby put to the breast within the first hour of life (PR = 1.63; 95%CI = 1.26−2.11). No association was observed with type of delivery or hospital status (public or private).ConclusionsA higher level of satisfaction with the childbirth experience is related to satisfactory antenatal care, a non-abusive, respectful, and informative environment during childbirth, and to the opportunity to breastfeed the baby within the first hour of life. In clinical practice, greater attention to these basic principles of care during pregnancy and delivery could provide more positive experiences during birth.     

On hysteretic vector autoregressive model with applications

This paper proposes a new hysteretic vector autoregressive (HVAR) model in which the regime switching may be delayed when the hysteresis variable lies in a hysteresis zone. We integrate an adapted multivariate Student-t distribution from amending the scale mixtures of normal distributions. This HVAR model allows for a higher degree of flexibility in the degrees of freedom for each time series. We use the proposed model to test for a causal relationship between any two target time series. Using posterior odds ratios, we overcome the limitations of the classical approach to multiple testing. Both simulated and real examples herein help illustrate the suggested methods. We apply the proposed HVAR model to investigate the causal relationship between the quarterly growth rates of gross domestic product of United Kingdom and United States. Moreover, we check the pairwise lagged dependence of daily PM2.5 levels in three districts of Taipei.     

Accurate computation of single and product moments of order statistics under progressive censoring

An accurate procedure is proposed to calculate approximate moments of progressive order statistics in the context of statistical inference for lifetime models. The study analyses the performance of power series expansion to approximate the moments for location and scale distributions with high precision and smaller deviations with respect to the exact values. A comparative analysis between exact and approximate methods is shown using some tables and figures. The different approximations are applied in two situations. First, we consider the problem of computing the large sample variance–covariance matrix of maximum likelihood estimators. We also use the approximations to obtain progressively censored sampling plans for log-normal distributed data. These problems illustrate that the presented procedure is highly useful to compute the moments with precision for numerous censoring patterns and, in many cases, is the only valid method because the exact calculation may not be applicable.     

Progressive censoring with fixed censoring times

In this paper, we revisit the progressive Type-I censoring scheme as it has originally been introduced by Cohen [Progressively censored samples in life testing. Technometrics. 1963;5(3):327–339]. In fact, original progressive Type-I censoring proceeds as progressive Type-II censoring but with fixed censoring times instead of failure time based censoring times. Apparently, a time truncation has been added to this censoring scheme by interpreting the final censoring time as a termination time. Therefore, not much work has been done on Cohens's original progressive censoring scheme with fixed censoring times. Thus, we discuss distributional results for this scheme and establish exact distributional results in likelihood inference for exponentially distributed lifetimes. In particular, we obtain the exact distribution of the maximum likelihood estimator (MLE). Further, the stochastic monotonicity of the MLE is verified in order to construct exact confidence intervals for both the scale parameter and the reliability.     

分利秩序、治理取向与场域耦合：一项来自“过渡型社区”的经验研究

城镇化推进下的“过渡型社区”成为城乡分治的模糊地带，利益和资源的不断输入，使得其治理主体和治理场域发生重构。基层治理视角下的村民自治被“分利性”进行价值侵占。就如何厘清“过渡型社区”利益博弈秩序中，出现“弱治理强分利”与“强治理弱分利”两种分化样态的内在机理与演化过程。基于绍兴安置社区、武汉城中村两地治理实践经验表明，在“国家 市场 社会”三重结构化关系中，社会治理单元在“城乡转变”过程中呈现出分利制度异化、农民利益外显、基层治理弱化等具体表征。其中治理主体、治理对象在“国家 市场 社会”场域耦合中形塑出的治理取向，揭示出国家基层治理现代化转型的多元面向。     

On the power of goodness-of-fit tests for the exponential distribution under progressive Type-II censoring

The aim of this article is to review existing goodness-of-fit tests for the exponential distribution under progressive Type-II censoring and to provide some new ideas and adjustments. In particular, we consider two-parameter exponentially distributed random variables and adapt the proposed test procedures to our scenario if necessary. Then, we compare their power by an extensive simulation study. Furthermore, we propose five new test procedures that provide reasonable alternatives to those already known.     

On MLEs of the parameters of a modified Weibull distribution based on record values

The modified Weibull distribution can be used quite effectively to model complex data from mechanical engineering or survival analysis studies that posses a monotonic or a bathtub-shape hazard rate. In this paper, we study the MLEs of the parameters of a modified Weibull distribution model in the presence of upper kth record values. The existence and uniqueness of the MLEs are proven in this case. Real data analysis is performed for illustrative purposes.     

国有企业混合所有制改革下股东利益博弈分析

国有企业混合所有制改革是当前理论探讨的热点。以分权控制理论为基础,构建国有股东、民营股东和监督机构三方的利益博弈模型,并对模型进行分析。结果显示,国有股东侵占民营股东的概率受监督机构监督成本和国有股东被监督损失等因素的影响,监督机构选择自主监督国有股东的概率受国有股东侵占行为惩罚力度系数、国有股东侵占额外收益和民营股东诉讼赔偿等因素影响。要加强对国有股东的惩罚力度,发挥好政府的监督作用,增强中小股东权利保障机制,推进国有企业混合所有制改革的步伐。     

Inference and optimal design of multiple constant-stress testing for generalized half-normal distribution under type-II progressive censoring

The generalized half-normal (GHN) distribution and progressive type-II censoring are considered in this article for studying some statistical inferences of constant-stress accelerated life testing. The EM algorithm is considered to calculate the maximum likelihood estimates. Fisher information matrix is formed depending on the missing information law and it is utilized for structuring the asymptomatic confidence intervals. Further, interval estimation is discussed through bootstrap intervals. The Tierney and Kadane method, importance sampling procedure and Metropolis-Hastings algorithm are utilized to compute Bayesian estimates. Furthermore, predictive estimates for censored data and the related prediction intervals are obtained. We consider three optimality criteria to find out the optimal stress level. A real data set is used to illustrate the importance of GHN distribution as an alternative lifetime model for well-known distributions. Finally, a simulation study is provided with discussion.     

Confidence regions for Pareto parameters from a single and independent samples

[Abstract] Based on a single and on two independent samples, joint confidence regions for parameters of Pareto distributions are proposed with minimum volume properties and without assigning the confidence level to dimensions. In the one-sample case, comparisons are made to former simultaneous confidence sets for Pareto parameters by means of simulation and a real data set. The two-sample case is studied in various set-ups and comprises simultaneous confidence regions for the shape parameters, the scale parameters, and higher-dimensional vectors of these parameters, where common shape and common scale models are also considered.