From Data to Causes: Building a General Cross-Lagged Panel Model (causality talk 3)

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This talk was delivered by Michael Zyphur on March 30th, 2021 as part of a conference on causality funded through the MEL-BER Partnership -- the University of Melbourne and the Berlin Universities Alliance (BUA). Details are as follows:

TITLE:
From Data to Causes: Building a General Cross-Lagged Panel Model

ABSTRACT:
This talk recaps the key points about some ways to model dynamic systems defined by autoregressive parameters with stochastic inputs with panel data in a structural equation modeling (SEM) framework. The usefulness of moving average parameters as well as accounting for stable factors such as personality traits (for individuals) or culture (for groups, organizations, or countries) is described and linked to SEM parameters. The underlying theory of causality that follows is based on an assumption of random errors and additional information on this approach can be found in the following papers and online talks:

From Data to Causes I: https://journals.sagepub.com/doi/abs/...
From Data to Causes II: https://journals.sagepub.com/doi/full...
From Data to Causes III: https://www.frontiersin.org/articles/...
Longer talk on these models:    • From Data to Causes I: Building a Gen...  

BIO:
Michael J. Zyphur received a PhD in I/O Psychology from Tulane University and is currently an Associate Professor of Business & Economics at the University of Melbourne.