Creating a reference to a complex emergency situation using time series methods: war in Guinea-Bissau 1998-1999

Impacts of complex emergencies or relief interventions have often been evaluated by absolute mortality compared to international standardized mortality rates. A better evaluation would be to compare with local baseline mortality of the affected populations. A projection of population-based survival data into time of emergency or intervention based on information from before the emergency may create a local baseline reference. We find a log-transformed Gaussian time series model where standard errors of the estimated rates are included in the variance to have the best forecasting capacity. However, if time-at-risk during the forecasted period is known then forecasting might be done using a Poisson time series model with overdispersion. Whatever, the standard error of the estimated rates must be included in the variance of the model either in an additive form in a Gaussian model or in a multiplicative form by overdispersion in a Poisson model. Data on which the forecasting is based must be modelled carefully concerning not only calendar-time trends but also periods with excessive frequency of events (epidemics) and seasonal variations to eliminate residual autocorrelation and to make a proper reference for comparison, reflecting changes over time during the emergency. Hence, when modelled properly it is possible to predict a reference to an emergency-affected population based on local conditions. We predicted childhood mortality during the war in Guinea-Bissau 1998-1999. We found an increased mortality in the first half-year of the war and a mortality corresponding to the expected one in the last half-year of the war.     

Learning discrete decomposable graphical models via constraint optimization

Statistical model learning problems are traditionally solved using either heuristic greedy optimization or stochastic simulation, such as Markov chain Monte Carlo or simulated annealing. Recently, there has been an increasing interest in the use of combinatorial search methods, including those based on computational logic. Some of these methods are particularly attractive since they can also be successful in proving the global optimality of solutions, in contrast to stochastic algorithms that only guarantee optimality at the limit. Here we improve and generalize a recently introduced constraint-based method for learning undirected graphical models. The new method combines perfect elimination orderings with various strategies for solution pruning and offers a dramatic improvement both in terms of time and memory complexity. We also show that the method is capable of efficiently handling a more general class of models, called stratified/labeled graphical models, which have an astronomically larger model space.     

Robust Poisson likelihood estimation for frailty Cox models: A simulation study

Frailty models can be fit as mixed-effects Poisson models after transforming time-to-event data to the Poisson model framework. We assess, through simulations, the robustness of Poisson likelihood estimation for Cox proportional hazards models with log-normal frailties under misspecified frailty distribution. The log-gamma and Laplace distributions were used as true distributions for frailties on a natural log scale. Factors such as the magnitude of heterogeneity, censoring rate, number and sizes of groups were explored. In the simulations, the Poisson modeling approach that assumes log-normally distributed frailties provided accurate estimates of within- and between-group fixed effects even under a misspecified frailty distribution. Non-robust estimation of variance components was observed in the situations of substantial heterogeneity, large event rates, or high data dimensions.     

Comparative Journalism Research – An Overview

This overview focuses on the most common type of comparative journalism research, which is cross‐national comparative research. The overview presents a typology for different types of comparative journalism research, based on whether the research interest is in journalism as an activity or as a product; and, in the case of journalism as an activity, whether the interest is in the system level, the organizational level, or the individual level of journalism. The overview finds that the analysis of journalism on the individual level and of journalism as a product are the most common types of comparative research, whereas comparative analysis of journalism on the organizational level is much under‐studied.     

NEIGHBOURHOOD MANAGEMENT FOR INTEGRATIVE DISTRICT DEVELOPMENT

In Germany there is broad consensus that efficient implementation of programme objectives requires cooperative political and administrative structures as the basis for realizing measures, activities and mobilization and revitalization processes deemed necessary by the neighbourhood. Therefore neighbourhood management is regarded as a critical tool for handling the tasks and reaching the targets associated with integrative district development. However, this tool is interpreted and utilized in a different manner. This is reflected not only in the labels (district, area or neighbourhood management), but more emphatically in the various organizational forms employed, ranging from individual officials equipped with specific authority to complex structures involving different levels of municipal control and operation. This article presents the neighbourhood management concept developed and implemented in the framework of the ‘Socially Integrative City’.     

Understanding the Relationship Between Egalitarianism and Affective Bias: Avenues to Reducing Prejudice Among Adolescents

In an era during which affirmative action in education is in jeopardy, it is important to understand how the ideologies of high-status ethnic group members maintain (or reduce) social inequality. We examine the extent to which the relationship between egalitarianism and prejudice among European American and Asian American adolescents can be explained by outgroup orientation (i.e., how much one values interacting with members of other ethnic groups) and strength of identification with one's ethnic group. Using structural equation modeling, we tested whether these two variables mediate the relationship between egalitarianism and intergroup prejudice. Results revealed that outgroup orientation was a mediator, but ethnic identity was not. Implications for mutual acculturation theory, prejudice-reduction programs, and affirmative action in education are discussed.     

The Value of Safety as Revealed in the Swedish Car Market: An Application of the Hedonic Pricing Approach

In this article the hedonic regression technique is used to estimate the value of traffic safety, using information from the Swedish market for automobiles. The results from the study show that the market price of an automobile is negatively correlated with its inherent risk level, i.e. Swedish car consumers pay a safety premium for safer cars. In comparison to previous Swedish stated-preference studies, this study reveals a lower willingness to pay for additional car safety, which might be a result of the interaction between government interventions and individual self-insurance and self-protection.JEL Classification: C51, D61, J28