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Workshop 1 - The TwinLife study and behavioral genetic modeling
Volker Lang, Dr. Bastian Mönkediek
Datum: 08.10.2018 ics-Datei
The aim of this course is to familiarize social scientists with twin studies and related quantitative methods of behavioral genetic analysis on an introductory level. To these ends, the course will use a statistical software used by many social scientists - Stata - and a related program package especially developed for behavioral genetic modeling using Stata - the “acelong-package”. The applied part of the course will use examples in the area of empirical educational research based on data of the new German twin family panel - TwinLife. Over the next years, the TwinLife panel surveys more than 4,000 twin pairs and their families in a cohort sequential design. Substantially, TwinLife focuses on topics relevant for the development of social inequalities over the life course. Currently, the data of the first survey wave of TwinLife is available as a scientific use file at the GESIS data archive free of charge (dx.doi.org/doi:10.4232/1.12665).
Selected participants will have the opportunity to present and discuss their own research ideas or projects in the form of a poster presentation with the lecturers and participants of the workshop in the evening of October 8, 2018. Participants interested in a poster presentation are asked to apply by submitting a short outline (about 0.5 pages) of their research idea or research project until August 20, 2018. Click here to submit your application.
Please remember to first book your workshop(s) and then apply for the poster presentation.
If you have questions regarding the workshop content or the application for the poster presentation please contact Dr. Nora Müller email@example.com
For organizational questions, please send an e-mail to Loretta Langendörfer firstname.lastname@example.org
Social scientist interested in behavioural genetic research, especially in standard quantitative analytic methods used in twin studies.
You can understand and apply basic behavioral genetic models (e.g., ACE variance decompositions). You can integrate behavioral genetic methods into standard social science analyses (e.g., regression models).
Participants should have basic knowledge about using Stata as well as regression and/or variance analysis. Basic knowledge about multilevel and/or structural equation modeling is an advantage.