Determinants and Consequences of Social Trust*

This article provides an overview of social trust, examining its various aspects and components. Trust is best understood in a sociological sense by focusing on its important relational characteristic. Following this lead, the article discusses briefly how social trust relates to social capital and examines factors that shape the development of social trust, along with outcomes related to variations in trust, classifying them by analytical level (i.e., individual, community, group, organizational, and societal). The article concludes by assessing the strengths and weaknesses of existing research and by identifying some important questions that have not yet been adequately addressed.     

Low dose risk estimation via simultaneous statistical inferences

Summary.  The paper develops and studies simultaneous confidence bounds that are useful for making low dose inferences in quantitative risk analysis. Application is intended for risk assessment studies where human, animal or ecological data are used to set safe low dose levels of a toxic agent, but where study information is limited to high dose levels of the agent. Methods are derived for estimating simultaneous, one-sided, upper confidence limits on risk for end points measured on a continuous scale. From the simultaneous confidence bounds, lower confidence limits on the dose that is associated with a particular risk (often referred to as a bench-mark dose ) are calculated. An important feature of the simultaneous construction is that any inferences that are based on inverting the simultaneous confidence bounds apply automatically to inverse bounds on the bench-mark dose.     

The current state of the labor queue: National and regional Evidence

We employ vector autoregressive techniques to determine the current state of the labor queue. Unemployment rate differentials have narrowed in recent years, potentially due to a change in the queue ordering, though a tight labor market and a stable queue would yield similar results. We find no evidence that the queue ordering has changed, which brings into question the resiliency of gains made by minority groups. We employ the same techniques to reveal the state of the queue across geographic regions and find that substantial differences exist across regions, implying variation in the relative labor force status of demographic groups.     

土木工程类复合型执业人才培养的研究与实践

根据复合型执业人才培养模式的要求,对土木工程专业理论课程教学内容进行合并、增删、优化组合;在实践教学环节方面,安排大四学生在施工现场实践近1年,由项目经理、工程监理和发包方驻地工程师进行综合指导。理论与实践紧密结合的复合型执业人才培养的改革实践获得了极好的效果。     

Generalized additive models for location, scale and shape

Summary.  A general class of statistical models for a univariate response variable is presented which we call the generalized additive model for location, scale and shape (GAMLSS). The model assumes independent observations of the response variable y given the parameters, the explanatory variables and the values of the random effects. The distribution for the response variable in the GAMLSS can be selected from a very general family of distributions including highly skew or kurtotic continuous and discrete distributions. The systematic part of the model is expanded to allow modelling not only of the mean (or location) but also of the other parameters of the distribution of y , as parametric and/or additive nonparametric (smooth) functions of explanatory variables and/or random-effects terms. Maximum (penalized) likelihood estimation is used to fit the (non)parametric models. A Newton–Raphson or Fisher scoring algorithm is used to maximize the (penalized) likelihood. The additive terms in the model are fitted by using a backfitting algorithm. Censored data are easily incorporated into the framework. Five data sets from different fields of application are analysed to emphasize the generality of the GAMLSS class of models.     

Factor analysis for ranked data with application to a job selection attitude survey

Summary.  Factor analysis is a powerful tool to identify the common characteristics among a set of variables that are measured on a continuous scale. In the context of factor analysis for non-continuous-type data, most applications are restricted to item response data only. We extend the factor model to accommodate ranked data. The Monte Carlo expectation–maximization algorithm is used for parameter estimation at which the E-step is implemented via the Gibbs sampler. An analysis based on both complete and incomplete ranked data (e.g. rank the top q out of k items) is considered. Estimation of the factor scores is also discussed. The method proposed is applied to analyse a set of incomplete ranked data that were obtained from a survey that was carried out in GuangZhou, a major city in mainland China, to investigate the factors affecting people's attitude towards choosing jobs.     

Gender,lineage, and fertility‐related outcomes in Ghana

A growing literature examines the empirical relationship between the joint reproductive preferences of marital partners and reproductive outcomes in Africa. Less explored is how spousal power in decision making may be influenced by lineage type. Using pooled data from Ghana, we investigate how lineage affects gendered reproductive decision outcomes and find some evidence that matrilineal women are more able than nonmatrilineal women to translate their reproductive preferences into action consistent with their goals.     

Discrete time modelling of disease incidence time series by using Markov chain Monte Carlo methods

Summary.  A stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities.