Generalized Linear Latent Variable Modeling for Multi-Group Studies

ABSTRACT

Latent variable modeling is commonly used in behavioral, social, and medical science research. The models used in such analysis relate all observed variables to latent common factors. In many applications, the observations are highly non normal or discrete, e.g., polytomous responses or counts. The existing approaches for non normal observations can be considered lacking in several aspects, especially for multi-group samples situations. We propose a generalized linear model approach for multi-sample latent variable analysis that can handle a broad class of non normal and discrete observations, and that furnishes meaningful interpretation and inference in multi-group studies through maximum likelihood analysis. A Monte Carlo EM algorithm is proposed for parameter estimation. The convergence assessment and standard error estimation is addressed. Simulation studies are reported to show the usefulness of the our approach. An example from a substance abuse prevention study is also presented.     

Nonlinear Regression

It is often thought that regression data should be mean-centered before being diagnosed for collinearity (ill conditioning). This view is shown not generally to be correct. Such centering can mask elements of ill conditioning and produce meaningless and misleading collinearity diagnostics. In order to assess conditioning meaningfully, the data must be in a form that possesses structural interpretability.     

Multiple partitioning of multiplex signed networks: Application to European parliament votes

For more than a decade, graphs have been used to model the voting behavior taking place in parliaments. However, the methods described in the literature suffer from several limitations. The two main ones are that 1) they rely on some temporal integration of the raw data, which causes some information loss; and/or 2) they identify groups of antagonistic voters, but not the context associated with their occurrence. In this article, we propose a novel method taking advantage of multiplex signed graphs to solve both these issues. It consists in first partitioning separately each layer, before grouping these partitions by similarity. We show the interest of our approach by applying it to a European Parliament dataset.     

Preventing Domestic Violence by Changing Australian Gender Relations: Issues and Considerations

ABSTRACT

In recent years Australian governments have significantly refocused domestic violence policies to prioritise primary prevention strategies. The objective of such strategies is to change how Australians perceive, acknowledge, and respond to domestic violence as a gender-based problem. Recognising the value of these efforts to address oppressive cultural practices, we draw attention to limitations inherent in shifting culture as a means to prevent domestic violence. We demonstrate how governments may improve policy approaches by addressing the structural inequalities that have historically forced women into positions of subordination. This will help us move toward more effective and long-term solutions to domestic violence.

IMPLICATIONS

• Australian domestic violence policy must include structural and systems changes prioritising women’s equal rights in addition to equal opportunities.

• To change cultural attitudes and behaviours, we must alter the environment in which oppressions and opportunities are located.

• Social workers can shape the debate to ensure that changing culture to prevent domestic violence is conceptualised as part of a wider social and policy change agenda.

     

Reinforced structural holes

Holes in social structure are variably reinforced by the social organization around the hole. The more reinforced the hole, the greater the difficulty in bridging it, but the more likely a successful bridge will carry information novel, and so potentially valuable, to people on the other side. To study how reinforcement varies with access to structural holes, and the achievement associated with access, I propose a measure of access to reinforced structural holes (RSH), and present results predicting achievement in an integrated banker organization and a balkanized supply-chain organization. In both study populations, the people who have access to structural holes also have access to reinforced structural holes, and all measures of access have a statistically significant association with achievement. However, there is no consistent prediction advantage from incorporating reinforcement in measures of access to structural holes. The reinforced-holes measure predicts compensation better or as well as network constraint and betweenness, but is weaker or no better than a count of nonredundant contacts. I do not infer from the results a rank-order of alternative measures so much as substitutability. I expect achievement to be associated with access to structural holes, but I expect the association to vary across alternative measures depending on how achievement is achieved in a specific population.     

“绿色经济”视角下汽车消费税的政策效应

汽车消费税是降低汽车工业能源消耗和交通污染排放的重要手段。在汽车消费税"绿色政策"效应研究理论的基础上,通过构建虚拟变量和断点回归模型对1994-2014年中国汽车行业的相关数据进行实证分析。研究发现,在短期受"价格效应"的影响,汽车消费税抑制了汽车生产及使用环节的CO2排放量,并且促进了汽车行业的技术进步;在长期"反弹效应" "市场效应" "生产效应""替换效应"和"持续效应"的共同作用下,导致政策对CO2排放量的影响表现为负向效应。此外,政策的实施在增加小排量汽车销售量的同时降低了大排量汽车的销售量,但是对3.0~4.0升（含4.0升）以及4.0升以上排量汽车的销售量没有显著影响。鉴于此,提出完善汽车税收制度的改革建议,以期为下一步的政策制定提供参考依据。     

品牌、认证与消费者信任倾向——以有机牛奶为例

以山东省570个消费者样本为例,基于中欧比较视角,探究消费者对不同品牌或认证的有机牛奶的信任倾向,并运用结构方程模型分析了消费者信任的前因。结果表明,消费者个体特征、感知价值、有机食品知识及行业环境对消费者信任产生显著正向影响,而食品安全意识和信息交流对信任的影响较为复杂;消费者对中欧品牌或中欧认证的信任存在差异,形成前因也略有不同。提升公众消费信心,应着力于推动有机知识宣传普及、增加消费者体验以及强化行业监管,乳品企业应根据消费者中外品牌或认证信任的差异制定相应的营销策略。     

Comparing two measures of creatinine clearance: an application of errors-in-variables and bootstrap techniques

Two indices of creatinine clearance (an index of kidney function) are compared on a group of cancer patients who underwent chemotherapy with a potentially nephrotoxic drug. The standard index, measured creatinine clearance MCC, is cumbersome to use, whereas the more convenient alternative, estimated creatinine clearance ECC, has not yet been conclusively evaluated on cancer patients. We conclude that under certain clinical conditions ECC and MCC are identically calibrated for males, but not for females, and we obtain estimated true and false positive rates for assessing the use of ECC instead of MCC as a diagnostic tool. We use a model that is formally equivalent to an errors-in-variables model with (unbalanced) repeated observations and correlated measurement errors. The bootstrap is used to obtain standard errors and confidence limits.     

An Exploratory Analysis of the Value of the Skills of IT Personnel: Their Relationship to IS Infrastructure and Competitive Advantage

Determining and assessing the requisite skills of information technology (IT) personnel have become critical as the value of IT has risen in modern organizations. In addition to technical skills traditionally expected of IT personnel, softer skills like managerial, business, and interpersonal skills have been increasingly cited in previous studies as mandatory for these employees. This paper uses a typology of IT personnel skills—technology management skills, business functional skills, interpersonal skills, and technical skills—and investigates their relationships to two information systems (IS) success variables, IS infrastructure flexibility and the competitive advantage provided by IS. The study investigates these relationships using the perceptions of chief information officers (CIOs) from mostly Fortune 2000 companies. The contributions of this study are: IT personnel skills do affect IS success, technical skills are viewed as the most important skill set in affecting IS infrastructure flexibility and competitive advantage, and modularity is viewed as more valuable to competitive advantage than integration. Several explanations are offered for the lack of positive relationships between the softer IT personnel skills and the dimensions of IS success used in this study.     

投资品相对价格、技术冲击与劳动要素投入——基于RBC观点的一个实证研究

本文由实证层面详细地考察了中性的与投资技术冲击对于我国劳动就业的宏观动态影响.基于投资品相对价格的长期趋势特征,我们发现:在长期限制识别条件下,正向的投资(中性)技术冲击对于劳动就业具有明显的促进作用(负向的抑制效应).这意味着,仅考虑单一中性技术冲击的SVAR模型混淆了不同性质的技术冲击对于劳动就业的不同影响.