This professional development workshop will guide participants through the steps required to analyze longitudinal or other time-series data sets using latent change score modelling. Latent change score modelling (LCS) is a flexible technique that can be used to analyze dynamic, multivariate, and bivariate associations within time-series data, including discrete changes between time points as well as constant change across the observation period – making it particularly valuable to researchers interested in modelling variable change over time. In this workshop, attendees will be challenged to re-think what it means to “measure change” within management research – and will be presented with a practical, step-by-step interactive tutorial that covers how to run and interpret the results of an LCS analysis, using R. By the end of the workshop, attendees will leave with not only knowledge of LCS modelling and when it is appropriate – but also, a functional, documented R script for running this analysis; a slide deck that explains step-by-step how each stage of the process works; and, an understanding of how to apply LCS both conceptually and practically to address a wide variety of research questions.
To get the most out of this PDW, attendees are encouraged to bring a laptop or other electronic device with an up-to-date installation of R and (optionally) R Studio.
