Title: The EffectLiteR Package for Analyzing Causal Effects Using Structural
Equation Modeling

Author: Axel Mayer

Affiliation: RWTH Aachen University

Abstract:
The analysis of causal effects is an important topic in the social and
behavioral sciences. Manually specifying an adequate statistical model and
computing average and conditional causal effects can become cumbersome in
models with latent variables, categorical covariates and higher-order
interactions. In this talk, we therefore illustrate the R package EffectLiteR
that makes a detailed analysis of effects conveniently accessible for applied
researchers. EffectLiteR includes a graphical user interface and is based on
the R package lavaan for structural equation modeling. We show how EffectLiteR
can be used to analyze different kinds of average and conditional effects
using a comprehensive example with an unbalanced 3 (treatment groups) by 2
(values of a categorical covariate) design, a latent outcome variable, and a
latent pretest. Finally, we provide an overview of further research and
current developments in the EffectLiteR approach. In particular, we will
present ideas related to order constrained hypotheses for average and
conditional effects and for extensions to multilevel designs.