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.     

Marginal and association regression models for longitudinal binary data with drop‐outs: A likelihood‐based approach

Longitudinal data often contain missing observations, and it is in general difficult to justify particular missing data mechanisms, whether random or not, that may be hard to distinguish. The authors describe a likelihood‐based approach to estimating both the mean response and association parameters for longitudinal binary data with drop‐outs. They specify marginal and dependence structures as regression models which link the responses to the covariates. They illustrate their approach using a data set from the Waterloo Smoking Prevention Project They also report the results of simulation studies carried out to assess the performance of their technique under various circumstances.     

2½‐Year‐Old Children Use Animacy and Syntax to Learn a New Noun

We examine how attention to animacy information may contribute to children's developing knowledge of language. This research extends beyond prior research in that children were shown dynamic events with novel entities, and were asked not only to comprehend sentences but to use sentence structure to infer the meaning of a new word. In a 4 × 3 design, animacy status (e.g., animate agent, inanimate patient) and labeling syntax (agent, patient, nonlabel control) were varied. Across most events, 2 1/2‐year‐old participants responded as if they expected animate entities to be named. However, in a prototypical (animate agent‐inanimate patient) event condition, children responded differentially across different syntactic structures. Thus, the clearest evidence for attention to syntactic cues was found in the prototypical event condition. These results suggest that young children attend to the animacy status of unfamiliar entities, that they have expectations about animacy relations in events, and that these expectations support emerging syntactic knowledge.     

Estimation of Metabolic Rate Constants in PBPK‐Models from Liver Slice Experiments: What Are the Experimental Needs?

A mechanistic model is presented describing the clearance of a compound in a precision-cut liver slice that is incubated in a culture medium. The problem of estimating metabolic rate constants in PBPK models from liver slice experiments is discussed using identifiability analysis. From the identifiability problem analysis, it appears that in addition to the clearance, the compound's free fraction in the slice and the diffusion rate of the exchange of the compound between culture medium and liver slice should be identified. In addition, knowledge of the culture medium volume, the slice volume, the compound's free fraction, and octanol-water-based partition between medium and slice is presupposed. The formal solution for identification is discussed from the perspective of experimental practice. A formally necessary condition for identification is the sampling of parent compound in liver slice or culture medium. However, due to experimental limitations and errors, sampling the parent compound in the slice together with additional sampling of metabolite pooled from the medium and the slice is required for identification in practice. Moreover, it appears that identification results are unreliable when the value of the intrinsic clearance exceeds the value of the diffusion coefficient, a condition to be verified a posteriori.     

An Existential Approach to Risk Perception

Existential, or existential-phenomenological philosophical approaches to the social psychology of risk perception provide a novel framework for understanding issues that are common to all humanity, such as fear of death, freedom and responsibility, isolation and meaninglessness, as these anxieties are a function of existing, or being-in-the-world. These fundamental anxieties can be related theoretically to the ways people perceive risks within social and cultural milieus, and can also be used practically within case studies, as demonstrated in the three examples presented, which examine perceptions of climate change, food-related risks, and environmental awareness via a mixture of quantitative and qualitative techniques. The discussion focuses on the possible insights that can be gained from taking an existential perspective on risk perception, and relates notions of contemporary technologically-oriented societies to the existential challenges faced by individuals and societies in the contemporary world.     

PREDICTING MARITAL SUCCESS FOR PREMARITAL COUPLE TYPES BASED ON PREPARE

Recent studies have shown that group differences in marital stability and satisfaction can be predicted based on premarital relationship quality. There is also a growing literature indicating that there are distinct types of relationships, both premaritally and developmentally over time. This study examined the relationship between the four premarital types (Vitalized, Harmonious, Traditional, and Conflicted) identified by Fowers and Olson (1992) and relationship outcome over a 3-year period with 393 couples. A substantial relationship was found, with conflicted couples being the most likely to separate or divorce. Vitalized couples had the highest levels of satisfaction, followed by Harmonious, Traditional, and Conflicted couples. Traditional couples were less likely to have divorced than Harmonious couples, even though Harmonious couples had higher premarital relationship satisfaction scores.     

Scheduling Updates of Probabilistic Risk Assessments: The Arkansas Nuclear One-Unit 1 Experience

This paper presents the results of a study that identified how often a probabilistic risk assessment (PRA)should be updated to accommodate the changes that take place at nuclear power plants. Based on a 7-year analysis of design and procedural changes at one plant, we consider 5 years to be the maximum interval for updating PRAs. This conclusion is preliminary because it is based on the review of changes that occurred at a single plant, and it addresses only PRAs that involve a Level 1 analysis (i.e., a PRA including calculation of core damage frequency only). Nevertheless, this conclusion indicates that maintaining a useful PRA requires periodic updating efforts. However, the need for this periodic update stems only partly from the number of changes that can be expected to take place at nuclear power plants–changes that individually have only a moderate to minor impact on the PRA, but whose combined impact is substantial and necessitates a PRA update. Additionally, a comparison of two generations of PRAs performed about 5 years apart indicates that PRAs must be periodically updated to reflect the evolution of PRA methods. The most desirable updating interval depends on these two technical considerations as well as the cost of updating the PRA. (Cost considerations, however, were beyond the scope of this study.)