Risk of Error and the Kappa Coefficient of a Binary Diagnostic Test in the Presence of Partial Verification

The accuracy of a binary diagnostic test is usually measured in terms of its sensitivity and its specificity, or through positive and negative predictive values. Another way to describe the validity of a binary diagnostic test is the risk of error and the kappa coefficient of the risk of error. The risk of error is the average loss that is caused when incorrectly classifying a non-diseased or a diseased patient, and the kappa coefficient of the risk of error is a measure of the agreement between the diagnostic test and the gold standard. In the presence of partial verification of the disease, the disease status of some patients is unknown, and therefore the evaluation of a diagnostic test cannot be carried out through the traditional method. In this paper, we have deduced the maximum likelihood estimators and variances of the risk of error and of the kappa coefficient of the risk of error in the presence of partial verification of the disease. Simulation experiments have been carried out to study the effect of the verification probabilities on the coverage of the confidence interval of the kappa coefficient.     

Population Change and Changing Educational Attainment of Ethnic Groups in the United States, 1980–2000

This study assesses the effect of population change on decade changes in the educational attainments of country of origin populations in the United States. Our data are derived from decennial censuses, NLMS, the World Bank, and INS. We find that changes in the share of country of origin populations with one or more years of post-secondary schooling are associated with selected components of population change during the 1980–1990 and 1990–2000 decades. The specific components include survivors during the decade, in-migration, and emigration of the foreign-born. Likewise, intra-generational mobility is found to be an important determinant of changes in educational attainment. The discussion addresses limitations of the data and suggests directions for future research as well as policy implications.     

Mixing patterns between age groups in social networks

We present a method for estimating transmission matrices that describe the mixing and the probability of infection between age groups. Transmission matrices can be used to estimate age-dependent forces of infection in age-structured, compartmental models for the study of infectious diseases. We analyze the social network generated by the synthetic population of Portland and extract mixing patterns. Our results show that the mixing within the population consists of two groups, children and adults. Children interact most frequently with other children close to their own age, while adults interact with a wider range of age groups and the durations of typical adult contacts are shorter than typical contacts between children. Furthermore, the transmission matrix shows that children are more likely to acquire infection than adults.     

Perceptions and expectations of price changes and inflation: A review and conceptual framework

Drawing on relevant literature from a diverse range of academic disciplines we present a conceptual framework intended to further our understanding of perceptions and expectations of price changes and inflation. Based on this framework, we provide a detailed review of the literature and an analysis of open issues in current research. The review is primarily concerned with individuals’ perceptions and expectations of price changes and inflation, which can influence individuals’ economic behaviour (e.g. spending and saving decisions). The main insight from the review is that while consumers may have a limited ability to store and recall specific prices, and even succumb to a number of biases in the way in which they form perceptions and expectations of global price changes, they do seem to have some feel for, and ability to judge and forecast, inflation. How they achieve this, however, is still an open question, although plausible explanations have been proposed. While much important research has been undertaken and significant progress made in our understanding of the psychology of inflation, there remain many unanswered questions and interesting avenues for future research, which are discussed in the final part of the paper.     

Basic notions for the analysis of large two-mode networks

Many large real-world networks actually have a two-mode nature: their nodes may be separated into two classes, the links being between nodes of different classes only. Despite this, and despite the fact that many ad hoc tools have been designed for the study of special cases, very few exist to analyse (describe, extract relevant information) such networks in a systematic way. We propose here an extension of the most basic notions used nowadays to analyse large one-mode networks (the classical case) to the two-mode case. To achieve this, we introduce a set of simple statistics, which we discuss by comparing their values on a representative set of real-world networks and on their random versions. This makes it possible to evaluate their relevance in capturing properties of interest in two-mode networks.     

Violence Exposure and Drug Use in Central American Youth: Family Cohesion and Parental Monitoring as Protective Factors

Associations between witnessing serious violence and drug use, and the protective influences of family cohesion and parental monitoring, were investigated among 9,840 adolescents (50.5% female, M age=15.29 years, SD=1.76) living in Panama and Costa Rica. After accounting for demographics and parental and sibling substance use, witnessing serious violence was associated with greater drunkenness, tobacco use, number of illicit drugs used, and problems with drugs and alcohol. In every analysis, exposure to violence was associated with more drug use, while family cohesion and parental monitoring attenuated risk. Further, family cohesion and parental monitoring exerted a protective‐stabilizing effect on number of illicit drugs used and on problems with drugs and alcohol. There were few interactions with age. Implications for prevention are discussed.     

Poverty statics and dynamics: does the accounting period matter?

Any public policy aimed at reducing the effects of deprivation should be aware of the consequences of the use of different income accounting periods on eligibility and subsequent policy evaluation. This study aims to throw some light on the relev-ance of choosing a specific accounting period for public policy evaluation in a European country, in contrast to the existing evidence for the United States. Our analysis indicates that there are some significant differences in the results on poverty when using different income accounting periods. Researchers and decision-makers using an annual income measure, whatever the economic and social welfare context, should be aware that the use of quarterly data instead of yearly data will lead to a significantly larger number of poor households and a lower level of inequality and mobility in the distribution.     

An interactional model of questions as therapeutic interventions

We dedicate this article to the memory of Steve de Shazer, who was the University's External Examiner for the doctoral dissertation on which this article is based. His comments were both generous and influential, as they were on many other occasions. We would also like to thank Ron Chenail (as Editor of JMFT ) and Dora Fried Schnitman (as Editor of Sistemas Familiares) for coordinating the simultaneous review and publication of this article in English and Spanish.     

Emotions into Disorder: Anxiety Disorders and the Social Meaning of Fear

This article explores what we refer to as norm-stimuli-state discrepancies, which are disparities between people's physical-emotional responses to emotional cues and the normative meanings of those cues. Drawing on forty qualitative interviews and participant observation research at support groups, we show that people with anxiety disorders describe two forms of norm-stimuli-state discrepancies. The first form involves discrepancies of type, in which people label fearful emotional states as deviant for being caused by the “wrong” stimuli. The second involves discrepancies of intensity, in which people label fearful states as deviant for involving feelings or displays of “too much” anxiety in response to an “appropriate” stimuli. The article further addresses the role of stimuli in prompting treatment seeking. Unexpected and intense emotional distress in combination with the falling away of external cues—which we refer to as “stimuli-less fear”—serve as a critical juncture on the path to an anxiety disorder diagnosis.