A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

民族社会学视野下的回族女性研究

回族女性研究是中国妇女研究的重要组成部分,20世纪90年代以来,中国回族女性研究取得了长足的进步和发展。本文着力于回顾既往回族女性研究中所涉及的诸多问题展开历史追溯与反思,就回族女性研究的内涵、研究的对象与范围、研究的意义与作用、研究的方法、理论构建、学术素养等学术界较为关注的几个问题进行了论述,在追溯中反思我们今后研究的拓展方向,力求为未来回族女性的发展提供一定参考。     

近十年来土族研究综述

本文从历史、语言文字、文学艺术、宗教文化、婚姻家庭、经济发展等方面 ,对土族近十年来的研究状况作了总结 ,可资参考     

北亚突厥百年研究(1900-2000年)

突厥是生活在我国北方的一个游牧民族。其在公元六世纪中叶,兴起于今新疆东北部,势力扩大到漠北、漠南及中亚一带,衰于八世纪中叶。本文综述阿尔泰以东的突厥即传统上所说的东突厥的范围近百余年的研究。包括族源、族属、社会性质、社会经济、语言、文字、习俗、宗教、碑文、官号、与周边各族各国间的关系和其他方面的内容。通过这些研究,可以发现我国学者在百年来对突厥巨大成就,使国际学术同行了解我国学者在这一领域取得的成果,促进此方面的进一步研究。该文可能对方家一些著述有遗漏,或者评述失当之处,请予指教。     

Mixed-effects Models with Skewed Distributions for Time-varying Decay Rate in HIV Dynamics

After initiation of treatment, HIV viral load has multiphasic changes, which indicates that the viral decay rate is a time-varying process. Mixed-effects models with different time-varying decay rate functions have been proposed in literature. However, there are two unresolved critical issues: (i) it is not clear which model is more appropriate for practical use, and (ii) the model random errors are commonly assumed to follow a normal distribution, which may be unrealistic and can obscure important features of within- and among-subject variations. Because asymmetry of HIV viral load data is still noticeable even after transformation, it is important to use a more general distribution family that enables the unrealistic normal assumption to be relaxed. We developed skew-elliptical (SE) Bayesian mixed-effects models by considering the model random errors to have an SE distribution. We compared the performance among five SE models that have different time-varying decay rate functions. For each model, we also contrasted the performance under different model random error assumptions such as normal, Student-t, skew-normal, or skew-t distribution. Two AIDS clinical trial datasets were used to illustrate the proposed models and methods. The results indicate that the model with a time-varying viral decay rate that has two exponential components is preferred. Among the four distribution assumptions, the skew-t and skew-normal models provided better fitting to the data than normal or Student-t model, suggesting that it is important to assume a model with a skewed distribution in order to achieve reasonable results when the data exhibit skewness.     

Investigating impacts of complex sampling on latent growth curve modelling

We investigate the impacts of complex sampling on point and standard error estimates in latent growth curve modelling of survey data. Methodological issues are illustrated with empirical evidence from the analysis of longitudinal data on life satisfaction trajectories using data from the British Household Panel Survey, a national representative survey in Great Britain. A multi-process second-order latent growth curve model with conditional linear growth is used to study variation in the two perceived life satisfaction latent factors considered. The benefits of accounting for the complex survey design are considered, including obtaining unbiased both point and standard error estimates, and therefore correctly specified confidence intervals and statistical tests. We conclude that, even for the rather elaborated longitudinal data models that were considered, estimation procedures are affected by variance-inflating impacts of complex sampling.     

Goodness-of-fit tests of generalized linear mixed models for repeated ordinal responses

Categorical longitudinal data are frequently applied in a variety of fields, and are commonly fitted by generalized linear mixed models (GLMMs) and generalized estimating equations models. The cumulative logit is one of the useful link functions to deal with the problem involving repeated ordinal responses. To check the adequacy of the GLMMs with cumulative logit link function, two goodness-of-fit tests constructed by the unweighted sum of squared model residuals using numerical integration and bootstrap resampling technique are proposed. The empirical type I error rates and powers of the proposed tests are examined by simulation studies. The ordinal longitudinal studies are utilized to illustrate the application of the two proposed tests.     

Intergenerational class mobility in contemporary Britain: political concerns and empirical findings

In Britain in recent years social mobility has become a topic of central political concern, primarily as a result of the effort made by New Labour to make equality of opportunity rather than equality of condition a focus of policy. Questions of the level, pattern and trend of mobility thus bear directly on the relevance of New Labour's policy analysis, and in turn are likely be crucial to the evaluation of its performance in government. However, politically motivated discussion of social mobility often reveals an inadequate grasp of both empirical and analytical issues. We provide new evidence relevant to the assessment of social mobility - in particular, intergenerational class mobility - in contemporary Britain through cross-cohort analyses based on the NCDS and BCS datasets which we can relate to earlier cross-sectional analyses based on the GHS. We find that, contrary to what seems now widely supposed, there is no evidence that absolute mobility rates are falling; but, for men, the balance of upward and downward movement is becoming less favourable. This is overwhelmingly the result of class structural change. Relative mobility rates, for both men and women, remain essentially constant, although there are possible indications of a declining propensity for long-range mobility. We conclude that under present day structural conditions there can be no return to the generally rising rates of upward mobility that characterized the middle decades of the twentieth century - unless this is achieved through changing relative rates in the direction of greater equality or, that is, of greater fluidity. But this would then produce rising rates of downward mobility to exactly the same extent - an outcome apparently unappreciated by, and unlikely to be congenial to, politicians preoccupied with winning the electoral 'middle ground'.     

‘Actually There is a Brain in There’: Uncovering Complexity in Pathways Through Education for Young Adults Who Have Been in Care

Internationally, research has highlighted disruption to the educational trajectories of young people in care, documenting concern about upheaval and poor educational outcomes. We present findings from English data arising from qualitative longitudinal research with care experienced people (16–32 years) who were also in education, employment or training. The analysis extends understanding of the experiences of those who achieve educational ‘success’, including those who followed non‐linear trajectories. The need for a flexible education system, and leaving care entitlements, which take into account the disruption experienced by young people in care and the consequent possibility of delayed educational pathways, is discussed.     

The nested joint clustering via Dirichlet process mixture model

This article focuses on the clustering problem based on Dirichlet process (DP) mixtures. To model both time invariant and temporal patterns, different from other existing clustering methods, the proposed semi-parametric model is flexible in that both the common and unique patterns are taken into account simultaneously. Furthermore, by jointly clustering subjects and the associated variables, the intrinsic complex shared patterns among subjects and among variables are expected to be captured. The number of clusters and cluster assignments are directly inferred with the use of DP. Simulation studies illustrate the effectiveness of the proposed method. An application to wheal size data is discussed with an aim of identifying novel temporal patterns among allergens within subject clusters.