Training Workshops on Modelling Mechanisms of Change Using Longitudinal Archived Data

Many social scientists are interested in investigating longitudinal change. For example, a educational researcher may be interested in how academic ability develops during childhood, an economist may be interested in how levels of personal debt changes during a recession, or a political scientist may be interested in how attitudes towards political parties change. There are now statistical methods available which are useful in describing the patterns of longitudinal change, both at the group level of the individual level. Latent growth models provide a powerful and flexible approach to describing longitudinal change.

Current developments in statistical modelling now allow social science researchers to move beyond simply describing longitudinal change and model the mechanisms and processes that underlie such changes. So, for example, a researcher could examine those individual (e.g. self-esteem, personality), social (e.g. socioeconomic status, parental educational achievement), and contextual (e.g. school and teacher characteristics) factors that may influence, or predict, how academic ability develops during childhood. This allows for the mechanisms and processes that determine change to be better understood. Such models can be formulated and tested using a flexible and powerful statistical framework known as latent variable modelling (LVM).

Although UK social scientists can avail of training in descriptive models of longitudinal change using LVM, there is no provision for comprehensive training in the use of those models that allow for the mechanisms and processes to be examined. This project aims to provide high quality training for UK social scientists in the application of these models. Workshops will be delivered three times a year, for three years, in three different locations (Belfast, London, and Stirling). Each workshop will last two days and comprise lectures and practical sessions. One important aspect of the workshops is that they will be based on datasets from the UK Data Archive which provides the largest collection of data in the social sciences in the UK. The benefits of using secondary data analysis have been demonstrated when there is clear integration of statistics and substantive issues. In order to maximise the impact of the workshops there will be follow-up webinars, the training materials from the workshops will also be archived on a dedicated website, and the specialist software will remain with the host institutions.

The programme of training will provide UK researchers and research students the opportunity to take part in training in state of the art statistical methods that allow complex hypotheses relating to the nature and mechanisms of change to be formulated and tested.

The outcomes of the training activities will produce:
*More social science researchers and research students with a broader knowledge and understanding of statistical models for the analysis of change and mechanisms of change.
*More social scientists that will be critical consumers of research published findings that employ longitudinal multivariate analysis.
*The potential for teaching academics who will incorporate more contemporary longitudinal multivariate analysis into their curriculum.
*An accessible resource of teaching and support materials to enhance analytic skills and knowledge in the area of longitudinal analysis.
*A portal to access the main sources of archived datasets in the UK.
*A long term understanding that data analysis is an integral part of the research process.
*Ongoing support and access to specialised software as a legacy of the project.