This is a past event
A 5-day course covering the design and analysis of intensive longitudinal studies.
Aim of the Course
In recent decades, researchers have become increasingly interested in understanding people's thoughts, emotions, and behaviors in their natural settings. The commonality in methods for doing so—experience sampling, daily diary, active and passive sensors, and ecological momentary assessment methods—is that they all involve intensive longitudinal assessments. These intensive longitudinal methods allow researchers to examine processes in daily life in a way that is not possible using traditional methods. Researchers can obtain repeated observations over the course of hours, days, and weeks, and often even longer.
Intensive longitudinal data, however, present multiple design and data analytic challenges stemming from the various possible sources of interdependence in these data. The multilevel or hierarchical linear model provides a flexible set of analytic tools that can take account of these complexities. But in order to run these analyses, the study design must be appropriate and missing data kept at a minimum.
Workshop Topics
- History and introduction to intensive longitudinal methods
- Designing an intensive longitudinal study
- Power/sample size analysis
- Analyzing the time course of intensive longitudinal data
- Analyzing within-person processes
- Categorical intensive longitudinal outcomes
- Psychometrics of intensive longitudinal data
- An introduction to mediation in intensive longitudinal data
The course will include lectures, software demonstrations, and computer lab work. In the data analysis examples, you can use various software packages that you are familiar with, including SPSS, SAS, R, and Mplus.
Who should attend?
For graduate students, postdocs and other researchers who have done intensive longitudinal studies or are planning them and want to learn more about state-of-the-art study design and data analysis.
Do I need to take the whole course?
The 5-day course is designed to cover both the design (Day 1-2) and data analysis (Day 3-5) part of intensive longitudinal studies. It is possible to attend only one part of the course. As a certain baseline level of knowledge will be assumed for those who only participate in the data analysis part of the course, please contact us to confirm eligibility.
Pre-requisites and Preparing for attendance
We assume little prior knowledge beyond linear regression models. To get the most out of the workshop, we recommend to bring your own laptop with SPSS or SAS or R and the Mplus demo version (here is a link to the Mplus demo version to download for free http://www.statmodel.com/demo.shtml) installed prior to the workshop. If you have already collected your own data please feel free to bring them and use them for analyses in the exercise sessions. We will also provide practice data sets. Reading Chapter 1 to 5 and 9 of Bolger and Laurenceau (2013) is also great if you want to prepare more.
Schedule:
The course is 9am – 5pm on Day 1-4, and 9am – 2pm on Day 5 with a subsequent sightseeing tour. We will have a workshop dinner on Tuesday evening starting at 6:30 pm.
Course fee:
The fee includes handouts, lunch, coffee breaks, the workshop dinner and the sightseeing tour. It does not cover travel and accommodation costs.
Early bird (ends April 16th, 2018)- Full course: £800.00
- Intro & Design only: £400.00
- Data Analysis only: £600.00
- Full course: £950.00
- Intro & Design only: £500.00
- Data Analysis only: £700.00
Cancellation:
Participants may cancel their booking by email, however the first £150 of any booking fee is non-refundable. Cancellations after 16th April 2018 are non-refundable.
By completing the application form, you are accepting these cancellation terms.
- Speaker
- Prof. Niall Bolger, Dr. Gertraud Stadler, Dr. Daniel Powell
- Hosted by
- University of Aberdeen
- Venue
- MacRobert Building
- Contact
-
Applications:
We have limited places on this workshop. If you would like to attend, please email the attached form to our workshop administrator Lyn Ajanaku at lyn.ajanaku@abdn.ac.uk. Lyn is also happy to receive any enquiries.