Dyadic Data Analysis Using Multilevel Modeling with R
June 19th-23rd, 2017
Instructors: David A. Kenny & Randi Garcia
The workshop on dyadic data analysis will focus on data where both members of a dyad are measured on the same set of variables. Among the topics to be covered are the actor-partner interdependence model, the analysis of distinguishable and indistinguishable dyads, mediation and moderation of dyadic effects, and over-time analyses of dyadic data. All analyses will be conducted using R, but no prior knowledge or experience with R is required. Participants are expected to have a working knowledge of multiple regression or analysis of variance.
Should I Attend?
We presume the variables you want to analyze are from two people who are measured on the SAME variables. For instance, you have data from husbands and wives who are both measured on satisfaction, commitment, and equity. If you have data from two people and say you have social support measured from one person and pain from the other person, the methods that we describe would be of little benefit to you. Second, we presume that each person is a member of one and only one dyad. If you have data where all possible dyads are formed from a group of people or people have dyadic relationships with the same person (e.g., a teacher with students), much of what we cover would be of little benefit to you.
This one-week workshop on Dyadic Data Analysis will be held at the University of Connecticut from Monday, June 19, through Friday, June 23, 2017. The workshop focuses on the analysis of dyadic data when both members of a dyad are measured on the same variables. Almost all analyses will use R. Other methods could be used (e.g., Structural Equation Modeling) and other multilevel programs can be used (e.g., HLM), but in this workshop we focus on one program, mainly because of its wide accessibility and it is free. Moreover, we shall make available setups for HLM, SPSS and SAS for some of the analyses that we present. No prior familiarity with R is required.
Among the topics to be covered are the vocabulary of dyadic analysis, non-independence, data structures, and the Actor-Partner Interdependence Model. We will also discuss mediation and moderation of dyadic effects and the analysis of over-time dyadic data (e.g., growth curve models). Participants will learn how to analyze dyadic data, and be able to interpret the results from their analyses. The discussion of over-time data is limited to one day and so the workshop should not be construed as workshop on longitudinal dyadic analysis.
It is expected that participants have a working knowledge of multiple regression. We extensively discuss the use of multilevel modeling, but participants need not be familiar in advance with this technique. Instruction consists of lecture, computer workshops, and individualized consultations. The emphasis will be practical with minimal emphasis on statistical theory, but those seeking more statistical information can arrange an individualized session with the instructors. A teaching assistant will also be available for consultation and assistance.
The computer workshop exclusively uses R. Several R setups and apps will be described for data organization, analysis, and write-ups. Although prior experience with the program is not required, it is desirable. Also in meetings with individual participants, alternative programs and approaches (e.g., SPSS, HLM, MLwiN, SAS, Amos, and Mplus) can be discussed. Neither instructor has much familiarity with Stata.
Participants are encouraged, but not required, to bring their own data so that they can apply these new methods to their own data. They should contact the staff beforehand to ensure that data are appropriately formatted for analysis. Normally SPSS sav or Excel files are acceptable.
The following materials and events are included in the cost of the workshop: · Binder with workshop outline, computer setups and outputs
- R programs to assist in the write-ups of the results of a dyadic analysis
- Meals: Continental breakfast each morning, complimentary luncheon Friday · Sunday pre-workshop reception
Recommended Advanced Reading:
Dyadic Data Analysis by Kenny, Kashy, and Cook, published by Guilford Press
Participants would benefit from reading Chapters 1, 2, 3, 4, 7, and 13 of the book in advance. Copies of these chapters and other readings will be distributed at the workshop.
- Monday – Thursday:
o 8:30am – 9:00am: Continental Breakfast
o 9:00am – 3:30pm: Workshop, including computer workshops
o 3:30pm – 5:00pm: Work on one’s own data; do an optional homework; individual meeting time with workshop instructors available
o 8:30am – 9:00am: Continental Breakfast o 9:00am – 12:00pm: Workshop
o 12:00pm: Complimentary Luncheon
Day 1: Introduction to the Dyadic Data
- Definitions: Distinguishability, Types of Variables, and Nonindependence · Estimating, Testing, and Interpreting Nonindependence
- Management of Dyadic Data: Data Structures and Data Restructuring · Using Multilevel Modeling with Dyadic Data
Day 2: The Actor-Partner Interdependence Model
- Estimation of Models for Indistinguishable Dyads · Estimation of Models for Distinguishable Dyads
- Power Analysis
- Testing Specialized APIM Models
- Testing for Indistinguishability
- Actor-Partner Interaction
- APIM apps
Day 3: The Actor-Partner Interdependence Model: Complications · Mediation of the APIM Effects
- Moderation of the APIM Effects Day 4: Over-Time Dyadic Data
- Repeated Measures Analysis
- Data Management Issues: Data Structure and Lagged Values · Growth-curve Models
- Stability-Influence Model
Day 5: Additional Topics
- Presenting Dyadic Data Analyses
- Using SEM with Dyadic Data
- Using GEE with Dyadic Data
- Alternative Dyadic Designs · Alternative Dyadic Models
The workshop runs Monday-Thursday from 9-5 and Friday from 9-12. A light continental breakfast is provided every morning, and the cost includes a closing group lunch on Friday from 12:00-1:00pm.