Analyzing Intensive Longitudinal Data: A Guide to Diary, Experience Sampling, and Ecological Momentary Assessment Methods (Amherst, MA)
- Niall Bolger, Columbia University
- Jean-Philippe Laurenceau, University of Delaware
Intensive longitudinal methods, often called experience sampling, daily diary, or ecological momentary assessment methods, allow researchers to study people's thoughts, emotions, and behaviors in their natural contexts. Typically they involve self-reports from individuals, dyads, families or other small groups over the course of hours, days, and weeks. Such data can reveal life as it is actually lived and provide insights that are not possible using conventional experimental or survey research methods. Intensive longitudinal data, however, present data analytic challenges stemming from the multiple levels of analysis and temporal dependencies in the data. The multilevel or mixed-effects model for longitudinal data is a flexible analytic tool that can take account of these complexities, and the goal of the 4-day workshop is to provide training in its use.
Drawn from the presenters' recent book, Intensive Longitudinal Methods (Guilford Press, 2013), course topics will include:
- History of intensive longitudinal methods and designs
- Time course analysis: Continuous outcomes
- Within-person causal processes: Continuous outcomes
- Dyadic intensive longitudinal data: Continuous outcomes
- Time course and causal processes: Categorical outcomes
- Psychometrics of intensive longitudinal data
- Statistical mediation in structural equation models of intensive longitudinal data
- Power analyses for intensive longitudinal designs
The course will include lectures, software demonstrations, and data analysis practice with example datasets and, if relevant, participants' own data. Various software packages will be used, including SAS, SPSS, R, and Mplus.
Prerequisites: We will assume that participants have taken a basic regression course and that they have collected or are interested in collecting intensive longitudinal data.
Fee: Members = $1600; Non-members = $3000
Location: University of Massachusetts -- Amherst, MA
Date(s): June 14 - June 17
Time: 9:00 AM - 5:00 PM