led by Dr Diarmuid McDonnell
Many interesting social phenomena follow processes of change that are not directly observable but can be inferred using statistical models. The classical example is the development trajectories of infants and children (e.g., height and weight) but many other outcomes are amenable to what are known as growth-curve analytical approaches e.g., career earnings trajectories, area-level change in business or charitable activity.
This one-day course will outline the fundamental concepts and approaches for estimating trajectories of change for social science phenomena, and includes practical examples and exercises using R and Stata.
It is most suited to empirical social science researchers with some experience of cross-sectional data and regression models, but will be of value to researchers from a wide range of disciplines.