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Strukturgleichungsmodelle

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Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften

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Zusammenfassung

Dieses Kapitel vermittelt folgende Lernziele: Vorteile von Strukturgleichungsmodellen für Datenanalysen kennen. Den Aufbau der Modelle und die dahinterstehenden Gleichungen verstehen. Verstehen, wie empirische Daten mit Strukturgleichungsmodellen analysiert werden. Einfache Analysen selbst durchführen und interpretieren können. Voraussetzungen und Probleme des Einsatzes von Strukturgleichungsmodellen kennen. Ergebnisse aus Analysen kritisch beurteilen können.

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Authors and Affiliations

  1. Psychologische Methodenlehre, Evaluation und Statistik, Psychologisches Institut der Universität Zürich, Binzmühlestrasse 14, Box 27, 8050, Zürich, Schweiz

    Christina Werner Dr.

  2. Abteilung Psychologische Methodenlehre, Evaluation und Forschungsmethodik,, Goethe-Universität Frankfurt am Main, Campus Westend, Grüneburgplatz 1, 60323, Frankfurt am Main, Deutschland

    Karin Schermelleh-Engel Apl. Prof. Dr.

  3. Abteilung Psychologische Methodenlehre, Evaluation und Forschungsmethodik, Goethe-Universität Frankfurt am Main, Campus Westend, Grüneburgplatz 1, 60323, Frankfurt am Main, Deutschland

    Carla Gerhard Dipl. -Psych.

  4. Methodenberatung für Bachelorstudierende, Goethe-Universität Frankfurt am Main, Campus Westend, Grüneburgplatz 1, 60323, Frankfurt am Main, Deutschland

    Jana Caroline Gäde Dipl. -Psych.

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  3. Carla Gerhard Dipl. -Psych.
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Werner, C., Schermelleh-Engel, K., Gerhard, C., Gäde, J.C. (2016). Strukturgleichungsmodelle. In: Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften. Springer-Lehrbuch. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41089-5_17

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  • DOI: https://doi.org/10.1007/978-3-642-41089-5_17

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