The ‘right time’ – negotiating the timing of interviews with vulnerable young people

Participant retention is a key factor in determining the success of longitudinal research. Challenges in re-locating and retaining participants over the long term are major issues for researchers working with young people who face adversity and experience frequent changes in circumstances. This article reports on a study of vulnerable young people and their transition into adulthood. Rather than the more conventional schedule-based approach to locating and re-interviewing young people, a relational process, the ‘right time’ framework, was used to facilitate young people's involvement in the study. Embedded in the ‘right time’ framework is recognition of the diverse and fluctuating circumstances that shape young people's availability for interviews. Several case examples are considered which amplify the way that the ‘right time’ framework allowed the research to navigate around these circumstances. The case examples highlight the value young people attached to being involved in the research, the influence on the ‘right time’ of wider relational tensions for young people and the need to negotiate researcher status as a different sort of adult. The ‘right time’ framework contributed to a high retention rate in the study generating a more representative sample and enhancing the subsequent data analysis by providing valuable insights into the lives of these vulnerable young people.     

Data tilting for time series

Summary. We develop a general methodology for tilting time series data. Attention is focused on a large class of regression problems, where errors are expressed through autoregressive processes. The class has a range of important applications and in the context of our work may be used to illustrate the application of tilting methods to interval estimation in regression, robust statistical inference and estimation subject to constraints. The method can be viewed as 'empirical likelihood with nuisance parameters'.     

西部人:价值观念的冲突与重构

论述了价值观念的含义、分类及演进过程 ,分析了西部人价值观念冲突的现状 ,指出 ,重构西部人价值观念 ,应进行产业、体制和环境等多因素的系统整合 ,确立西部大开发的主导价值观念 ,形成以主导价值观念为核心的价值观念系统 ,并把非理性的价值观念升华为理性的价值观念。     

Shrinkage confidence intervals for the normal mean: Using a guess for greater efficiency

If the unknown mean of a univariate population is sufficiently close to the value of an initial guess then an appropriate shrinkage estimator has smaller average squared error than the sample mean. This principle has been known for some time, but it does not appear to have found extension to problems of interval estimation. The author presents valid two‐sided 95% and 99% “shrinkage” confidence intervals for the mean of a normal distribution. These intervals are narrower than the usual interval based on the Student distribution when the population mean lies in such an “effective interval.” A reduction of 20% in the mean width of the interval is possible when the population mean is sufficiently close to the value of the guess. The author also describes a modification to existing shrinkage point estimators of the general univariate mean that enables the effective interval to be enlarged.     

投资者信心和中国宏观经济波动——基于MIDAS混频模型

将投资者信心指数引入MIDAS混频模型之中,可以考察新冠疫情背景下投资者信心对于中国宏观经济波动的影响。基于投资者信心指数和“三驾马车”对我国季度GDP增长率进行预测,通过实证发现:引入投资者信心指数的MIDAS混频模型在预测精准度方面和基准模型进行比较,预测精准度高于未加入投资者信心的模型,均方根残差比值更小;在多元MIDAS混频模型之中,加入投资者信心指数的回归模型对我国GDP的实时预报和短期预测结果更加稳定,可为决策者提供更加精确的参考区间;宏观经济的波动对投资者信心指数变化反应,和投资、消费和进出口相比是最灵敏的。这为定量追踪宏观经济波动提供了一个新的视角。     

Testing Inference in Inflated Beta Regressions under Model Misspecification

We consider testing inference in inflated beta regressions subject to model misspecification. In particular, quasi-z tests based on sandwich covariance matrix estimators are described and their finite sample behavior is investigated via Monte Carlo simulations. The numerical evidence shows that quasi-z testing inference can be considerably more accurate than inference made through the usual z tests, especially when there is model misspecification. Interval estimation is also considered. We also present an empirical application that uses real (not simulated) data.     

The ‘affective security curriculum’: breeding JBs through the marriage of the academic and the jingoistic

How does the US recruit its citizen spies used to maintain and proliferate coercive power? I use an interdisciplinary approach and a framework of affect theory to argue that there is an ‘affective security curriculum’ (ASC) that assists in explaining the tendencies towards jingoism used in the recruitment and indoctrination of students – as future security workers – in certain academic disciplines. The ASC is precisely the phenomenon that works to construct this expert class and is produced by order words, the most crucial of which is ‘terrorism’, as well as larger cultural norms linked to neoliberalism that have achieved near total dominance since the 1980s. The ASC works by intensifying the (in)ability to act for those in its domain. The necessity of linguistically proficient security workers to the US’ hegemonic project makes this a question of considerable political importance. The ASC is a different approach to answering questions of how US hegemony is maintained. Whereas positivist research agendas, such as content analysis, and postpositivist approaches, such as critical discourse analysis, certainly have their uses (and to which my notion of ASC is indebted), paradigms such as these fail to focus on the engendering processes at work vis-à-vis the expert class, without which the discursive frames such methodologies analyse would simply dissipate. My overarching purpose in this paper is to develop the concept of the ASC, its quiddity, and to present at least an incipient methodology for analysing its critical duties. As my primary intent is to introduce and conceptualize the theoretical framework of the affective security curriculum, the applied segment of this endeavour will be relatively brief – and is designed as a primer for further research.     

Smooth tail-index estimation

The two parametric distribution functions appearing in the extreme-value theory – the generalized extreme-value distribution and the generalized Pareto distribution – have log-concave densities if the extreme-value index γ∈[?1, 0]. Replacing the order statistics in tail-index estimators by their corresponding quantiles from the distribution function that is based on the estimated log-concave density ? f _n leads to novel smooth quantile and tail-index estimators. These new estimators aim at estimating the tail index especially in small samples. Acting as a smoother of the empirical distribution function, the log-concave distribution function estimator reduces estimation variability to a much greater extent than it introduces bias. As a consequence, Monte Carlo simulations demonstrate that the smoothed version of the estimators are well superior to their non-smoothed counterparts, in terms of mean-squared error.     

基层党员坚定“四个自信”的实证研究——以浙江省嵊泗县为例

“四个自信”是党的最新理论成果，其对基层党员的影响理应是深远的。通过问卷、访谈以及文献分析等方法调查了以浙江省嵊泗县为代表的基层党员对“四个自信”的坚定状况。调研结果表明：其在总体上的坚定情况是可喜的，但也存在不少问题。通过对比参与调查的基层党员和非党员对在中国特色社会主义理论、道路、制度和文化等方面的差异，从民生问题、贫富差距扩大趋势、理论宣传教育程度和发展实际问题等方面分析原因，并据此提出了相应对策。     

Improved approaches to interval estimation of effective doses for a logistic dose-response curve

Asymptotic confidence (delta) intervals and intervals based upon the use of Fieller's theorem are alternative methods for constructing intervals for the <$>\gamma<$>% effective doses (ED<$>_\gamma<$>). Sitter and Wu (1993) provided a comparison of the two approaches for the ED<$>_{50}<$>, for the case in which a logistic dose response curve is assumed. They showed that the Fieller intervals are generally superior. In this paper, we introduce two new families of intervals, both of which include the delta and Fieller intervals as special cases. In addition we consider interval estimation of the ED<$>_{90}<$> as well as the ED<$>_{50}<$>. We provide a comparison of the various methods for the problem of constructing a confidence interval for the ED<$>_\gamma<$>.