Welcome to the Thomas Ledermann Method Lab
- Analysis of data from dyads and triads
- Analysis of group composition in dyads and triads
- Analysis of similarity in dyads and triads
- Analysis of Mediation and Moderation
- Analysis of Longitudinal Data
- Mixture Modeling
- R programming
- Interpersonal Relationships
Joseph W. Jones is a graduate student in the EAPS program with an emphasis in Quantitative Psychology. His research interests are in longitudinal data analyses applied to developmental and health psychology. He has experience with a broad scope of analysis techniques, including multilevel modeling, structural equation modeling, and mixture modeling. In addition, he has experience using these analytic techniques in SPSS, Mplus, and R. His substantive interests are in developmental psychology with a focus on how cognition and health, both mental and physical, change over time. Recently, he began working on datasets with older adults (65+ years) assessing the relationship between rates of change on several aspects of physical and mental health.
Thomas Ledermann is Assistant Professor in Psychology at Utah State University. He has published on dyadic data analysis, mediation and moderation, the analysis of change, and the assessment of spcific effects and contrasts in structural equation models. The journals the works were published include the Journal of Family Psychology, Psychological Methods, Structural Equation Modeling, Personal Relationships, and Journal of Social and Personal Relationships. Thomas Ledermann currently serves as consulting editor of the Journal of Family Psychology and is on the editorial board for Personal Relationships. More information about Thomas Ledermann can be found on the faculty webpage.
Ledermann, T., Rudaz, M., & Grob, A. (2017). Analysis of group composition in multimember multigroup data. Personal Relationships, 24, 242-264.
Garcia, R., Kenny, D. A., & Ledermann, T. (2015). Moderation in the actor-partner interdependence model. Personal Relationships, 22, 8-29.
Ledermann, T., & Macho, S. (2014). Analyzing change at the dyadic level: The Common Fate Growth Model. Journal of Family Psychology, 28, 204-213.
Ledermann, T., & Kenny, D. A. (2012). The common fate model for dyadic data: Variations of a theoretically important but underutilized model. Journal of Family Psychology, 26, 140-148.
Ledermann, T., Macho, S., & Kenny, D. A. (2011). Assessing mediation in dyadic data using the actor-partner interdependence model. Structural Equation Modeling, 18, 595-612.
Macho, S., & Ledermann, T. (2011). Estimating, testing, and comparing specific effects in structural equation models: The phantom model approach. Psychological Methods, 16, 34-43.
Kenny, D. A., & Ledermann, T. (2010). Detecting, measuring, and testing dyadic patterns in the Actor-Partner Interdependence Model. Journal of Family Psychology, 24, 359-366.
RDDD – Restructure and Describe Dyadic Data. R program with graphical user interface co-written with David A. Kenny. Reference: Ledermann, T., & Kenny, D. A. (2015). A toolbox with programs to restructure and describe dyadic data. Journal of Social and Personal Relationships, 22, 8-29.