Meta-analysis using multilevel models with an application to the study of class size effects

Meta-analysis is formulated as a special case of a multilevel (hierarchical data) model in which the highest level is that of the study and the lowest level that of an observation on an individual respondent. Studies can be combined within a single model where the responses occur at different levels of the data hierarchy and efficient estimates are obtained. An example is given from studies of class sizes and achievement in schools, where study data are available at the aggregate level in terms of overall mean values for classes of different sizes, and also at the student level.     

Flash Flood Risks and Warning Decisions: A Mental Models Study of Forecasters,Public Officials,and Media Broadcasters in Boulder,Colorado

Timely warning communication and decision making are critical for reducing harm from flash flooding. To help understand and improve extreme weather risk communication and management, this study uses a mental models research approach to investigate the flash flood warning system and its risk decision context. Data were collected in the Boulder, Colorado area from mental models interviews with forecasters, public officials, and media broadcasters, who each make important interacting decisions in the warning system, and from a group modeling session with forecasters. Analysis of the data informed development of a decision‐focused model of the flash flood warning system that integrates the professionals’ perspectives. Comparative analysis of individual and group data with this model characterizes how these professionals conceptualize flash flood risks and associated uncertainty; create and disseminate flash flood warning information; and perceive how warning information is (and should be) used in their own and others’ decisions. The analysis indicates that warning system functioning would benefit from professionals developing a clearer, shared understanding of flash flood risks and the warning system, across their areas of expertise and job roles. Given the challenges in risk communication and decision making for complex, rapidly evolving hazards such as flash floods, another priority is development of improved warning content to help members of the public protect themselves when needed. Also important is professional communication with members of the public about allocation of responsibilities for managing flash flood risks, as well as improved system‐wide management of uncertainty in decisions.     

A Comparison of Infants' Categorization in Paired and Successive Presentation Familiarization Tasks

Three experiments directly compared infants' categorization in variations of the visual familiarization task. In each experiment, 4‐ or 6‐month‐old infants were familiarized with a collection of dogs or cats and then their response to novel dogs and cats was assessed. In Experiment 1, 4‐month‐old infants responded to the exclusive distinction of dogs or cats when tested in a paired‐comparison task. In Experiments 2 and 3, 6‐month‐old infants, but not 4‐month‐old infants, responded to this same distinction in a successive presentation task, even when the amount of familiarization was equated to that of the paired comparison task. Therefore, familiarization with a particular set of stimuli does not induce infants to respond to a single category but rather they respond to different categories depending on features of the task.     

NGOS AND THE DEVELOPMENT OF CIVIL SOCIETY IN BULGARIA AND THE USA

This study examines the development of civil society and its ability to facilitate stronger democratic practices in Bulgaria using the USA as a comparison. Using data gathered from surveys of NGOs in 2006, we examine three sets of questions. First, what is the level of NGO organizational capacity? Second, to what degree are NGOs performing their mediating roles? Third, how do NGOs perceive their effectiveness in working with the state and its citizens. Our findings suggest that Bulgarian NGOs face a number of challenges when compared with US NGOs, which affect their ability to engage in civil society activities such as establishing horizontal ties with citizens and other groups.     

Using recurrent time-to-event models with multinomial outcomes to generate toxicity profiles

Most clinical studies, which investigate the impact of therapy simultaneously, record the frequency of adverse events in order to monitor safety of the intervention. Study reports typically summarise adverse event data by tabulating the frequencies of the worst grade experienced but provide no details of the temporal profiles of specific types of adverse events. Such 'toxicity profiles' are potentially important tools in disease management and in the assessment of newer therapies including targeted treatments and immunotherapy where different types of toxicity may be more common at various times during long-term drug exposure. Toxicity profiles of commonly experienced adverse events occurring due to exposure to long-term treatment could assist in evaluating the costs of the health care benefits of therapy. We show how to generate toxicity profiles using an adaptation of the ordinal time-to-event model comprising of a two-step process, involving estimation of the multinomial response probabilities using multinomial logistic regression and combining these with recurrent time to event hazard estimates to produce cumulative event probabilities for each of the multinomial adverse event response categories. Such a model permits the simultaneous assessment of the risk of events over time and provides cumulative risk probabilities for each type of adverse event response. The method can be applied more generally by using different models to estimate outcome/response probabilities. The method is illustrated by developing toxicity profiles for three distinct types of adverse events associated with two treatment regimens for patients with advanced breast cancer.     

Evacuation from Natural Disasters: A Systematic Review of the Literature

Research on evacuation from natural disasters has been published across the peer‐reviewed literature among several disparate disciplinary outlets and has suggested a wide variety of predictors of evacuation behavior. We conducted a systematic review to summarize and evaluate the current literature on demographic, storm‐related, and psychosocial correlates of natural disaster evacuation behavior. Eighty‐three eligible papers utilizing 83 independent samples were identified. Risk perception was a consistent positive predictor of evacuation, as were several demographic indicators, prior evacuation behavior, and having an evacuation plan. The influence of prior experiences, self‐efficacy, personality, and links between expected and actual behavior were examined less frequently. Prospective, longitudinal designs are relatively uncommon. Although difficult to conduct in postdisaster settings, more prospective, methodologically rigorous studies would bolster inferences. Results synthesize the current body of literature on evacuation behavior and can help inform the design of more effective predisaster evacuation warnings and procedures.     

Perceptions of charisma from thin slices of behavior predict leadership prototypicality judgments

Signaling theory suggests that people use cues transmitted by leaders to form impressions of charisma but the validity of these impressions remains unexplored. Here, we examined whether perceptions of charisma from thin slices of nonverbal behavior relate to inferences based on more information. We tested whether ratings of charisma from 5-, 15-, and 30-s clips (with no audio) of speakers delivering a message predicted evaluations of vision articulation and leadership prototypicality made from 60-s multimedia clips (with audio). The results indicated that thin-slice charisma judgments predicted the criterion scores for leadership prototypicality but not vision articulation from all of the 5-, 15-, and 30-s silent clips. The current data therefore suggest that thin slices of charisma can be valid indicators of leadership.