GESIS Training Courses
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Administrative Koordination

Janina Götsche

Introduction to Behavioral Genetic Modeling using Stata

Dozent(en):
Volker Lang

Datum: 19.10.2020 ics-Datei

Veranstaltungsort: Online via Zoom / Course language: English

Referenteninformationen - Volker Lang

Seminarinhalt

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 deploy 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 utilze examples in the area of empirical educational research based on data of the German twin family panel - TwinLife. Over the next years, the TwinLife panel surveys more than 4,000 twin pairs and their families alternating with face-to-face and telephone interviews. Substantially, TwinLife focuses on topics relevant for the development of social inequalities over the life course. Currently, the data of the first face-to-face and the first telephone survey of TwinLife are available as a scientific use file at the GESIS data archive free of charge (dx.doi.org/doi:10.4232/1.13208). By the time of this course data of the second face-to-face interview will be available, too. 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.


Keywords



Zielgruppe

Social scientist interested in behavioural genetic research, especially in quantitative analytic methods used in twin studies.


Lernziel

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).


Voraussetzungen

Required: Basic knowledge about using Stata, basic knowledge about variance and/or regression analysis; advantageous: Basic knowledge about multilevel modelling and/or structural equation modelling.


Zeitplan

Literaturempfehlungen

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