Virtual Summer School
Intensive Longitudinal Methods & Dyadic Data Analysis
Designing and Analyzing Data from Ecological Momentary Assessment, Experience Sampling, Ambulatory Assessment, and Diary Studies in Individuals and Dyads
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About the Summer School
This Summer School expands over 5 weekly preliminary webinars in July and August and 7 days of virtual lectures and exercises in August (12th – 21st August, 2020).
We offer a 2 Day Summer School: Introduction to Intensive Longitudinal Methods and a 7 Day Summer School: Introduction to Intensive Longitudinal Methods & Dyadic Data Analysis as options for participating:
2 Day Summer School: Introduction to Intensive Longitudinal Methods: Consists of two days (part 1: 12th to 14th of August) of live virtual teaching and five preliminary webinars. This workshop is ideal for those who are beginning to work with longitudinal data.
7 Day Summer School: Introduction to Intensive Longitudinal Methods & Dyadic Data Analysis: Consists of seven days (part 1 & 2: 12th to 21st of August) of live virtual teaching and five preliminary webinars. The summer school is suitable for researchers who already have some experience with longitudinal data. Ideally you have data which you would like to analyze, but we will also provide practice data sets.
The course will include lectures, software demonstrations, computer lab work and consultations. In the data analysis examples, you can use various software packages that you are familiar with, including SPSS, SAS, R, and Mplus.
Topics Part 1: Intensive Longitudinal Methods
Part 1: Intensive Longitudinal Methods (ILM) (12th – 14th August, 2020)
The first part of the Summer School addresses methods to understand people's thoughts, emotions, and behaviors in their natural settings. These methods are known under a number of labels — experience sampling, daily diary, active and passive sensors, and ecological momentary assessment methods — and have in common that they all involve intensive longitudinal assessments. Intensive longitudinal methods allow researchers to examine processes in daily life beyond more 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 challenges for design and data analysis including the various possible sources of interdependence in the data. The study design must fit to the research questions and guard against missing data. Multilevel linear models provide a flexible set of analytic tools for these complexities.
Overview of topics covered in part 1
• History and introduction to intensive longitudinal methods
• Designing an intensive longitudinal study
• Analyzing the time course of intensive longitudinal data
• Analyzing intensive longitudinal interventions
• Analyzing within-person processes
• Categorical intensive longitudinal outcomes
• Psychometrics of intensive longitudinal data
Topics Part 2: Dyadic Data Analysis
Part 2: Dyadic Data Analysis (17th – 21st August, 2020)
The second part introduces cross-sectional and longitudinal dyadic data analysis. Close dyadic relationships, e.g. for marital partners, parent-child dyads, dating relationships, are often the most important contexts for human beings. Research investigating everyday human experience is increasingly examining these powerful influences on daily behavior, thoughts, and feelings. However, dyadic data present analytic challenges because they have
various sources of interdependence (e.g. non-independence between members of the dyad such as a parent and a child). Flexible analytic tools can accommodate these complexities. Participants of the course will gain a better understanding of dyadic data analysis in both cross-sectional and longitudinal contexts.
Overview of topics covered in part 2
Introduction to dyadic designs, dyadic data, and Interdependence
• Explaining dyadic covariation: The Actor-Partner Interdependence Model
• Brief Mplus tutorial
• Dyadic Score Model
• Visualizing dyadic data
• Two-wave dyadic data
• Dyadic growth curve modeling
• Multilevel dyadic process modeling
• Visualization & dyadic process model
• Power analysis for dyadic process model
For whom is this course?
For graduate students, postdocs and other researchers from Europe 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.
Pre-requisites and preparing for attendance
Depending on which option for participating you choose we assume different amounts of knowledge. For the 2-day workshop, we assume little prior knowledge beyond linear regression. For the Summer School we assume that you already have some knowledge in working with longitudinal data
To get the most out of the courses, 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.
Signing in starts on the 12th of August at 5pm (UTC +2). The same evening we will have an informal online gathering with some introductory input and the possibility to get to know each other. Teaching starts every day at 2pm and lasts till 6pm. The time before noon is reserved for the exercises.
We have limited places on this Summer School. Please complete the sign-up form to register your interest in attending and email it to email@example.com. You can download the sign-up form here.
Please note the last day for booking this course will be the 30th June, 2020. Please email firstname.lastname@example.org after that date to find out if there are still places available.
If you apply for student discount, please note that proof of student status will be required, e.g., student certificate with University stamp or ID card with expiry date. Student rate does not apply to Researchers, Academic Staff, and Private, Public and Charitable Sector Employees.
· After successful registration, a space is reserved for you in the course
· You will receive an invoice via E-Mail and Mail
· Please transfer the full amount within 30 days to the indicated bank account
· Only after a successful payment a space is guaranteed
Delegates may cancel their booking by email to email@example.com. However, the first 150€ of any booking fee is non-refundable. Cancellations after the 31st of May, 2020 are non-refundable.