Understanding Cumulative Risk Perception from Judgments and Choices: An Application to Flood Risks

Catastrophic events, such as floods, earthquakes, hurricanes, and tsunamis, are rare, yet the cumulative risk of each event occurring at least once over an extended time period can be substantial. In this work, we assess the perception of cumulative flood risks, how those perceptions affect the choice of insurance, and whether perceptions and choices are influenced by cumulative risk information. We find that participants' cumulative risk judgments are well represented by a bimodal distribution, with a group that severely underestimates the risk and a group that moderately overestimates it. Individuals who underestimate cumulative risks make more risk‐seeking choices compared to those who overestimate cumulative risks. Providing explicit cumulative risk information for relevant time periods, as opposed to annual probabilities, is an inexpensive and effective way to improve both the perception of cumulative risk and the choices people make to protect against that risk.     

Peer Crowd Affiliation and Internalizing Distress in Childhood and Adolescence: A Longitudinal Follow‐Back Study

Concurrent and longitudinal associations between peer crowd affiliation and internalized distress were examined in a sample of 246 youth (148 girls, 98 boys). Children completed measures of depression, social anxiety, loneliness, and self‐esteem when they were in grades 4 to 6 (Time 1), and again 6 years later during adolescence (grades 10 – 12; Time 2). At Time 2, adolescents also reported their self‐concept and their identification with reputation‐based peer crowds, including Populars, Jocks, Brains, Burnouts, Non‐Conformists, and None/Average crowds. Results indicated that adolescents' report of peer crowd affiliation was concurrently associated with self‐concept and levels of internalizing distress. Follow‐back analyses of internalizing trajectories revealed that Populars/Jocks had experienced significant declines in internalizing distress across development, whereas Brains exhibited some increases in internalizing distress between childhood and adolescence.     

A Bayesian Hierarchical Model for the Evaluation of a Website

Consider a website and the surfers visiting its pages. A typical issue of interest, for example while monitoring an advertising campaign, concerns whether a specific page has been designed successfully, i.e. is able to attract surfers or address them to other pages within the site. We assume that the surfing behaviour is fully described by the transition probabilities from one page to another, so that a clickstream (sequence of consecutively visited pages) can be viewed as a finite-state-space Markov chain. We then implement a variety of hierarchical prior distributions on the multivariate logits of the transition probabilities and define, for each page, a content effect and a link effect. The former measures the attractiveness of the page due to its contents, while the latter signals its ability to suggest further interesting links within the site. Moreover, we define an additional effect, representing overall page success, which incorporates both effects previously described. Using WinBUGS, we provide estimates and credible intervals for each of the above effects and rank pages accordingly.     

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.     

Odd-Burr generalized family of distributions with some applications

We study a new family of continuous distributions with two extra shape parameters called the Burr generalized family of distributions. We investigate the shapes of the density and hazard rate function. We derive explicit expressions for some of its mathematical quantities. The estimation of the model parameters is performed by maximum likelihood. We prove the flexibility of the new family by means of applications to two real data sets. Furthermore, we propose a new extended regression model based on the logarithm of the Burr generalized distribution. This model can be very useful to the analysis of real data and provide more realistic fits than other special regression models.     

The Decomposition of Economic Outcomes as a Result of Changes in Brazil’s Male Age–Education Structure

In Brazil, the age and education compositions of the male labor force is changing with great regional variation. Based on Demographic Census microdata, results indicate that cohort size has a negative impact on earnings, but this effect is decreasing over time. In this study we consider the impact on earnings by age and education, as well as estimated income inequality reduction and racial differentials. Fertility decline and improve regarding educational attainment had a significant influence on the decline of income inequality in the country. Moreover, the non-white population has been experiencing less success in relation to educational achievement, compared to the white population.     

Domestic violence screening and service acceptance among adult victims in a dependency court setting

Many child welfare systems are unable to effectively identify and address co-occurring domestic violence and child maltreatment. In response, the Dependency Court Intervention Program for Family Violence implemented a protocol to identify indicators of domestic violence in families involved with child protection proceedings. This article highlights data that demonstrate the ability of an outreach and screening process to identify adult victims of domestic violence in dependency court and to offer them appropriate intervention services.     

Why Digital Tools Have Not Yet Revolutionized Adolescent Health Research and What We Can Do

The promise of digital tools and devices for spurring new discoveries in adolescent health research is enticing. This special section draws attention to many of the advantages that mobile and wearable devices offer for ambulatory assessment research, which have now been realized. Despite such progress, digital tools have not yet delivered on their predicted revolution of adolescent health research. I offer four reasons for why digital devices have fallen short of this predicted promise. For each barrier, I suggest parallel strategies for ensuring adolescent research benefits from Ambulatory Assessment advances. To avoid missing out on opportunities to support young people, adolescence scholarship must develop in time with innovations in digital devices and platforms and move past what has, to date, been an overwhelming focus on fears about their usage.