Contribution analysis to analyze the effects of the health impact assessment at the local level: A case of urban revitalization

The health impact assessment (HIA) is a tool used to estimate the potential impact on health of non-health-related proposals prior to implementation. While it is increasingly used in Quebec, Canada, studies have not analyzed its medium-term impacts and potential long-term impacts. We conducted a contribution analysis using in-depth interviews with key stakeholders, as well as documents, observation and images related to HIA in order to analyze its impacts on the revitalization of road infrastructure, parks and green spaces, and residential housing. Our analysis not only reflects on the decision-making process through the adoption and implementation of HIA recommendations, but also on the link between actions implemented in the field and health outcomes.     

Perceptions of paternal involvement and labour pain management in Chinese couples during childbirth: A qualitative study

BackgroundLabour pain is an individual experience embedded in a socio-cultural context. In childbirth, the father’s involvement provides important support to the mother during labour. However, few published studies have evaluated couples’ experiences of paternal involvement and labour pain management in the Chinese context.AimThis study aimed to understand the experience of labour pain management and the father’s involvement in childbirth from the perspectives of women and their partners in Hong Kong.MethodsAn exploratory qualitative design was adopted. A purposive sample of 45 Chinese parents was recruited at the postnatal unit of a regional hospital. Data were collected through semi-structured face-to-face interviews within 1 month after birth. The data were subjected to content analysis.FindingsThe findings revealed six major themes: the mothers’ experience of labour pain, effectiveness of pain relief measures, mothers’ perceptions of support from their partners, mothers’ perceptions of support from healthcare professionals, fathers’ experience of involvement in childbirth and suggested improvements to maternity services.DiscussionChinese mothers experienced intense labour pain and used various pain relief measures. Both parents considered the involvement of fathers and support from healthcare professionals to be highly significant during childbirth.ConclusionsThis study highlights the need for a family-centred model of care during childbirth that involves both parents in the decision-making process. Chinese maternity services should implement individualised birth plans that acknowledge both parents’ expectations and preferences, thus promoting a positive childbirth experience for the parents.     

我国股东代表诉讼实用性的经济学分析

设置股东代表诉讼的目的是为了完善公司治理,强化股东的经营监督和抑制违法的作用。但由于股东提起代表诉讼是为了公司和全体股东的利益,如何降低原告股东的诉讼成本对实现股东代表诉讼的立法目的具有重要的意义。     

长三角地区农民资金互助合作社运行满意度及影响因素分析 ——以泰州市苏陈资金互助合作社为例

农民资金互助合作社是目前准新型农村金融机构在长三角地区的典型代表。基于对江苏省泰州市苏陈资金互助合作社的实地调研,重点考察社员对样本农民资金互助合作社运行的满意度及影响因素。研究发现：样本社社员对于农民资金互助合作社的整体运行情况基本持肯定态度;社员的家庭总收入、政府对农民资金互助合作社的支持力度以及社员在农民资金互助合作社借用的互助金额度,是影响社员对于农民资金互助合作社满意度的主要因素;农民资金互助合作社融资业务的开展,对于社员的农业和二三产业经营均具有正向促进作用;农民资金互助合作社的互助金投放的覆盖面与农村信用合作社等传统农村正规金融机构形成了互补关系。在此基础上,提出了相关政策建议。     

Diagnostics of multiple group influential observations for logistic regression models

In this paper, two new multiple influential observation detection methods, GCD.GSPR and mCD*, are introduced for logistic regression. The proposed diagnostic measures are compared with the generalized difference in fits (GDFFITS) and the generalized squared difference in beta (GSDFBETA), which are multiple influential diagnostics. The simulation study is conducted with one, two and five independent variable logistic regression models. The performance of the diagnostic measures is examined for a single contaminated independent variable for each model and in the case where all the independent variables are contaminated with certain contamination rates and intensity. In addition, the performance of the diagnostic measures is compared in terms of the correct identification rate and swamping rate via a frequently referred to data set in the literature.     

Toward an integrated Bayesian network approach to measurement error detection and correction

In this article, the quality of data produced by national statistical institutes and by governmental institutions is considered. In particular, the problem of measurement error is analyzed and an integrated Bayesian network decision support system based on non-parametric Bayesian networks is proposed for its detection and correction. Non-parametric Bayesian networks are graphical models expressing dependence structure via bivariate copulas associated to the edges of the graph. The network structure and the misreport probability are estimated using a validation sample. The Bayesian network model is proposed to decide: (i) which records have to be corrected; (ii) the kind and amount of correction to be adopted. The proposed correction procedure is applied to the Banca d’Italia Survey on Household Income and Wealth and, specifically, the bond amounts are analyzed. Finally, the sensitivity of the conditional distribution of the true value random variable given the observed one to different evidence configurations is studied.     

On Hotelling’s T2 test in a special paired sample case

In a special paired sample case, Hotelling’s T² test based on the differences of the paired random vectors is the likelihood ratio test for testing the hypothesis that the paired random vectors have the same mean; with respect to a special group of affine linear transformations it is the uniformly most powerful invariant test for the general alternative of a difference in mean. We present an elementary straightforward proof of this result. The likelihood ratio test for testing the hypothesis that the covariance structure is of the assumed special form is derived and discussed. Applications to real data are given.     

Estimation of the smallest scale parameter of two-parameter exponential distributions

Improved point and interval estimation of the smallest scale parameter of n independent populations following two-parameter exponential distributions are studied. The model is formulated in such a way that allows for treating the estimation of the smallest scale parameter as a problem of estimating an unrestricted scale parameter in the presence of a nuisance parameter. The classes of improved point and interval estimators are enriched with Stein-type, Brewster and Zidek-type, Maruyama-type and Strawderman-type improved estimators under both quadratic and entropy losses, whereas using as a criterion the coverage probability, with Stein-type, Brewster and Zidek-type, and Maruyama-type improved intervals. The sampling framework considered incorporates important life-testing schemes such as i.i.d. sampling, type-II censoring, progressive type-II censoring, adaptive progressive type-II censoring, and record values.     

Model selection for factor analysis: Some new criteria and performance comparisons

This paper derives Akaike information criterion (AIC), corrected AIC, the Bayesian information criterion (BIC) and Hannan and Quinn’s information criterion for approximate factor models assuming a large number of cross-sectional observations and studies the consistency properties of these information criteria. It also reports extensive simulation results comparing the performance of the extant and new procedures for the selection of the number of factors. The simulation results show the di?culty of determining which criterion performs best. In practice, it is advisable to consider several criteria at the same time, especially Hannan and Quinn’s information criterion, Bai and Ng’s IC_p2 and BIC₃, and Onatski’s and Ahn and Horenstein’s eigenvalue-based criteria. The model-selection criteria considered in this paper are also applied to Stock and Watson’s two macroeconomic data sets. The results differ considerably depending on the model-selection criterion in use, but evidence suggesting five factors for the first data and five to seven factors for the second data is obtainable.     

地区收入、食品价格与恩格尔系数

本文以2016年我国31个省级地区截面数据为样本,构建扩展模型考察恩格尔系数与收入、食品价格之间的关系。研究发现,恩格尔系数与地区收入存在显著的负相关性,纳入食品价格后收入对恩格尔系数的影响变得更为显著,二者关系满足恩格尔定律。恩格尔系数和以地区食品价格平价代表的食品价格之间显著正相关,若再考虑其他因素,则食品价格对恩格尔系数的影响会稍有减弱。进一步将食品区分为生活必需型食品与非生活必需型食品,测算得到的基本恩格尔系数、高阶恩格尔系数与收入之间仍呈负相关关系,但与基本恩格尔系数相比,高阶恩格尔系数与收入之间的负相关性更弱。恩格尔系数受生活必需型食品价格的影响强于非生活必需型食品价格的影响,基本恩格尔系数主要受生活必需型食品价格的影响,而高阶恩格尔系数同时受到两类食品价格的影响。