The ICVS in the developing world

The ICVS started in the industrialized world. However, its potential for providing information on crime and victimization from developing countries was immediately apparent. Since 1990 the participation of developing countries became larger and larger. As of today, 29 developing countries took part in the ICVS at least once. More have already expressed their interest in joining the project and will probably do so in 2004. The ICVS database on developing countries contains a wealth of information that has no precedents. The survey can provide an overview on crime and victimization problems rarely available in developing countries. Although comparisons with the industrialized countries may be difficult, the ICVS database represents one of the best sources to measure crime-related issues across the world.This article presents results from 23 main cities from three global regions: Africa, Asia, and Latin America. Developing countries very often show high victimization rates, especially for property-related crime. Crimes are reported to the police less frequently than in the industrialized world. Some types of crime, such as car hijacking in Southern Africa, reflect special risks run by citizens in specific parts of the world

Bayesian inference for psychology. Part II:Example applications with JASP

Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely. An important impediment to the widespread adoption of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for the analysis of almost every experiment: the t-test, ANOVA, correlation, regression, and contingency tables. In Part II of this series we introduce JASP (http://www.jasp-stats.org), an open-source, cross-platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in part on the Bayesian analyses implemented in Morey and Rouder’s BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian hypothesis testing are only a mouse click away