Home Studium Workshops / Konferenzen Videos Forschung Dienstleistungen Team
Impressum / Kontakt
deutschsprachige Version 
Besucher seit 27.02.2014:
ganze Website: 262605
aktuelle Seite: 780
Causal Effects EAM Fachgruppe Methoden und Evaluation (DGPs)

Kurse: Kursinformationen

en  Introduction to the Analysis of Causal Effects with EffectLite, LISREL and Mplus

Kursleitung: Prof. Dr. Rolf Steyer, Dipl.-Psych. Ulf Kröhne & Dipl.-Psych. MSc Steffi Pohl

Wintersemester 2005/2006, Workshop, Kurslänge: 12.25 Stunden, Sprache: Englisch, Thema: Analysis of causal effects

This course combines the theory of individual and average causal effects in the sense of J. Neyman and D. B. Rubin with analysis techniques of structural equation modelling. All designs and models for the analysis are developed for the purpose to learn about individual, conditional and/or average causal effects. Unlike other courses on the analysis of treatment effects, it uses structural equation modelling (with or without latent variables) instead of analysis of variance techniques, the General Linear Model or related techniques. As will be shown, this will enable us to learn not only about average and conditional effects, but, in specific models, also about individual causal effects.

This course is a synthesis of different traditions in methodology: Rubin's approach to causality, the Campbellian tradition of quasi-experimentation and internal validity, and structural equation modeling, especially latent state-trait modeling, latent change modeling and latent growth curve modeling.

Although this workshop does not require experience and knowledge in structural equation modelling (SEM), we do not recommend this workshop as a first introduction to SEM, if the motivation is to have an introduction into SEM. For this purpose we rather suggest our workshop "Erste Einführung in die Analyse von Strukturgleichungsmodellen mit LISREL" held in German in November 2005. Similar introduction in English is: "Analysis of Structural Equation Models with Lisrel 8.54" held in March 2004. (These workshops are still available in the internet and on DVDs).

The present workshop, "Introduction to the Analysis of Causal Effects with EffectLite, LISREL and Mplus" aims at those interested in data analysis in experimental and quasi-experimental studies involving covariates such as one or several pretests, a discrete treatment variable, and one or several outcome variables. EffectLite analyzes a generalized multivariate analysis of variance and covariance. It creates LISREL or Mplus input files, reads and interprets the results, computes some statistics, and produces an output file containing the most important results. EffectLite does not assume homogeneity of variances (in the univariate case with a single outcome variable) or covariance matrices (in the multivariate case with two or more outcome variables) of the outcome variables between groups. Furthermore, it allows analyzing mean differences between groups with respect to (a) several manifest outcome variables, (b) one or more latent outcome variables, and (c) a mixture of the two kinds of outcome variables. The results include estimates of conditional and average effects with respect to several manifest covariates or with respect to one or more latent covariates, and a mixture of the two kinds of covariates. The covariate(s) may also be qualitative. In this case we estimate and test average effects for non-orthogonal analysis of variance designs, provided that the covariates are specified as qualitative indicator variables. If the covariates fulfil certain assumptions, the program estimates and tests the average causal effects.

In the workshop we will:

  1. present the theory of individual and average causal effects,
  2. show how to use EffectLite, LISREL and Mplus for this class of models, and
  3. show how to use LISREL and Mplus for individual causal effect models.


Um die herunterladbaren Videos anzuschauen, benötigen Sie den RealPlayer, den Sie hier herunterladen können. Die Videos werden bereitgestellt über die Digitale Bibliothek Thüringen Digitale Bibliothek Thüringen (dbt). Die grün verlinkten Videos und Materialien sind kostenfrei abrufbar. Klicken Sie auf den grünen Link, um das Video zu sehen oder die Datei herunterzuladen! Um alle Materialien und Videos abrufen zu können, müssen Sie sich einloggen.

 
Individual and Average Causal Effects (Theory)
  • Motivation: The Simpson paradox
  • Basic concepts: Individual and average causal effects (ICEs and ACEs)
  • Fixed and random effects regression
  • Generalization to more than two treatment conditions
Identifying the average causal effect via mean differences (Theory)
  • The prima facie effect
  • Two kinds of biases
  • The role of randomization
  • Heterogeneity of variances between treatment groups
Estimating and testing average causal effects via structural equation modeling (Applications using LISREL and Mplus)
  • One outcome variable, two or more treatment groups
  • Several outcome variables, two or more treatment groups
  • One latent outcome variable, two or more treatment groups
  • Several latent outcomes
Conditional Causal Effects (Theory)
  • Conditional (average) causal effects
  • Conditional mean differences
Identifying conditional and average causal effect via conditional mean differences (Theory)
  • Sufficient conditions for unbiasedness of conditional mean differences
  • Understanding the sufficient conditions
Estimating and testing conditional and average causal effects via structural equation modeling (Applications using LISREL and Mplus)
  • Three kinds of covariates: manifest continuous, manifest nominal, latent continuous
  • Analysis of covariance, regression with interactions, nonorthogonal analysis of variance
  • One outcome variable, two or more treatment groups, one covariate
  • Several outcome variables, two or more treatment groups, one covariate
  • One latent outcome variable, two or more treatment groups, one covariate
  • Several latent outcomes and several latent covariates
Analysis of Individual and Average Causal Effects (Theory and Applications)
  1. A Single Group, two Pre-test and two Post-test Occasions
  2. Two Groups, two Pre-test and two Post-test Occasions
  3. Multitrait-multimethod analyses via ICE models


Videos


Session
Topic
Abstract
Presenter
Video-presentation with slides (Realplayer)
Video (RealPlayer)
Slides (PDF) & models
Blackboard pictures
01
Prima facie effects: Example 1 (Simpson paradox)
Rolf Steyer
02
Prima facie effects: Example 2 (Non-orthogonal ANOVA and using EffectLite for data analysis)
Rolf Steyer
03
Causal effects
Rolf Steyer
04
Prima facie effects and their relationship to causal effects
Rolf Steyer
05
Latent covariates and latent outcome variables
Rolf Steyer
 
06
LISREL input and output files for the analysis with latent covariate and outcome variables
Rolf Steyer
 
07
Modelling method effects as individual causal effects
Rolf Steyer
08
Individual and Average Causal Effects
Rolf Steyer & Steffi Pohl
09
A new multitrait-multimethod model
Steffi Pohl


Material

Readings Slides Excel sheets Data sets Models

Software

EffectLite LISREL Student Version