Training Workshops on Modelling Mechanisms of Change Using Longitudinal Archived Data

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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.