ABSTRACT
This chapter will provide guidance on the management and analysis of Experience Sampling Method (ESM) data. Firstly, the management of ESM data will be presented; how the data structure is defined and how to set up an ESM dataset. The analysis of ESM data will be outlined in terms of multilevel modelling. A short introduction to random effects models for multilevel data will be presented, describing analysis approaches for concurrent and time lagged data, and how to examine moderation in an ESM setting. Suggestions on how to summarize the different levels of ESM data will then be presented, followed by some considerations for missing data. Finally, an application of these methods will be presented on an example ESM dataset, assessing the relationship between mood and paranoia in people with psychosis. Throughout the chapter, the aim will be to help researchers understand how statistical methods can be used to understand ESM data and how they can be utilized in order to answer specific research questions.
