Universität Wien

220078 SE SE Advanced Data Analysis 3 (2017W)

Prüfungsimmanente Lehrveranstaltung

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 30 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Mo, 6.11. 9.30-17Uhr PC- Labor UZA II
Do, 9.11. 9.30-17Uhr PC-Labor UZA II
Fr, 10.11. 9.30-17Uhr PC-Labor UZA II
Do, 7.12. 9.30-17Uhr PC-Labor UZA II
Do, 14.12. 9.30-17Uhr PC-Labor UZA II
Mo, 8.1. 9.30-17Uhr PC-Labor UZA II
Do, 11.1. 9.30-17Uhr PC-Labor UZA II

Mittwoch 24.01. 09:45 - 12:15 Seminarraum 2, Währinger Straße 29 1.UG

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

The objective of this course is to introduce students to the core methods and processes of structural equation modeling (SEM), a family of statistical approaches able to explore complex relationships between and amongst latent and observed variables. In particular, participating students will develop a fundamental understanding of the following topics:

Basics of SEM and how it differs from other statistical methods (e.g., multiple regression)
Strategies for model specification, identification, estimation, and determining fit
Confirmatory factor analysis
Structural models
Mediation and moderation in a structural framework
Combining measurement and structural models

As this is an introductory course, we will focus on applying SEM methods to non-nested, cross-sectional, and continuous variables. Emphasis will be placed on the practical applications of SEM and latent variable techniques to address relevant questions in communications and the social sciences more broadly. Course lectures, readings, and assignments will reflect this applied focus, and will help students to develop appropriate analytic plans and interpret results in addition to teaching them how to conduct analyses using AMOS software.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Class participation and preparedness (25%)
Online quiz (25%)
Homework assignments (50%)

Mindestanforderungen und Beurteilungsmaßstab

For successfully passing the course, participants have to achieve at least 51% of the total points. Full details on the course grading (e.g., grading system) will be given in the first session.

Prüfungsstoff

Literatur

Kline, R. B. (2011): Principles and Practice of Structural Equation Modeling, 3rd edition, The Guilford Press (ISBN 978-1-60623-877-6). (Or more recent editions.)

And materials (e.g., articles) provided via Moodle.

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mo 07.09.2020 15:39