Introduction to Understanding Society using Stata
Researchers interested in learning how to access and analyse Understanding Society data using Stata can attend a two-day training course running Nov 25-26 at the University of Essex.
The course is aimed at new users of the survey, as well as those who have so far made use only of simpler aspects of the data. It is run by a team of Understanding Society experts based at the home of the study, the Institute for Social and Economic Research, University of Essex.
Course tutor, Dr Gundi Knies said:
“The underlying structure of Understanding Society is complex, with various different data about individuals and the households in which they live. New and innovative features of the survey also add other layers of complexity. Analysing such data require good understanding of the structure as well as the complex sample design.”
Gundi added that while the survey team had endeavoured to make this structure as transparent as possible through the way data are organised, the number of different data sets could appear daunting to researchers looking to use the data for the first time.
By the end of the two day course, participants will have a thorough knowledge of Understanding Society, from survey design to data-set structure, and will have the tools to make the most of a rich, but complex, data set.
The course aims to guide data users through some of the study’s complexities, and ensure that they can effectively make use of as much of the data as they require for their own research projects.
The main focus is on the data reorganisation techniques required for different types of cross-sectional and longitudinal research, rather than the statistical techniques themselves, but it is informed by the ways in which data require to be organised for different statistical techniques. The course also provides information and guidance on the weights provided in the study and examples of how these may be used.
Places for the courses fill up very fast, so researchers are urged to register now to avoid disappointment.