When: 9th – 13th of June
Where: Linnæus University, Sweden
The course aims at promoting a general overview of methods, including experiments and simulation, and research questions typical of micro-sociology, social psychology, and other behaviorally oriented disciplines. It will also show how these instruments can be applied to improve our understanding of important social facets, such as social norms, social influence, collective action, and group identity.
The course is based on two lectures per day, Monday, June 9 to Friday, June 13. It will include both classroom lectures and laboratory activities. The latter ones are designed to give students a direct experience of participating in and running behavioral experiments and will present running examples of known simulation models.
When: 12th – 13th June, 2014
Where: University of Southampton, Southampton
This course will focus on the application of linear mixed models for medical applications with a continuous outcome. Topics will include simple and more complex hierarchical data structure such as repeated measurements on patients within wards within hospitals, crossed and nested effects, fixed and random effects as well as random coefficient models. The course will give an introduction to the general mixed model and highlight its ability to cope with potentially nested fixed and random effects simultaneously. Data structures with repeated measures in time will also be touched upon. All models will be illustrated at hand of study data. The course will include a mixture of lectures and practical workshops using the software STATA.
The course is aimed at researchers who want to perform linear mixed model analysis and/or need to analyse hierarchically structured study data. Participants may be academic researchers in the Medical and Health or Social Sciences sector or may work within the Government, pharmaceutical industry, or other parts of the private sector.
Participants are expected to have a good working knowledge of simple statistical methods, including a basic understanding of regression and analysis of variance. No familiarity with the software STATA is required.