EIGHT MYTHS ABOUT CAUSALITY AND STRUCTURAL EQUATION MODELS

By Kenneth A. Bollen, Judea Pearl. 2013

652 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Sociology and Political Science, Statistics and Probability

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Citations in the corpus

External Validity: From Do-Calculus to Transportability Across Populations (2014, methodology): “3We use the acronym SEM for both parametric and nonparametric representations though, historically, SEM practitioners preferred the former (Bollen and Pearl, 2013).”
Interpretation and identification of causal mediation. (2014, neutral): “25The testable implications of causal diagrams are discussed in Appendix A (see Bollen and Pearl, 2013; Pearl, 2009b, pp. 140–144.”
Police Body-Worn Cameras: Effects on Officers’ Burnout and Perceived Organizational Support (2018, methodology): “Identifiability also depends on justifying each directed path in the model as a causal relationship (Bollen & Pearl, 2013; Kline, 2010; McDonald & Ho, 2002) and explaining omitted paths.”
Achieving sustainable development goals: predicaments and strategies (2019, background): “Contrary to some confusion in the literature (Wilkinson 1999), SEM analysis produces quantitative causal claims, conditional on the input assumptions, along with data fitness and well-defined tests (Pearl 2012; Bollen and Pearl 2013; Tarka 2018).”
piecewiseSEM: Piecewise structural equation modelling in r for ecology, evolution, and systematics (2015, background): “While an in-depth discussion of causality is beyond the scope of this paper, further discussion of causality and how it relates to SEM can be found in: Pearl (2012) and Bollen & Pearl (2013).”
Enhancing Rigor in Quantitative Entrepreneurship Research (2019, background): “…when advocating for the PO framework (Rubin, 1974) for causal inference, structural equation modeling (SEM) has previously been falsely portrayed as an incompatible (and as an inferior approach for causal inference) approach without recognizing their equivalency (Bollen & Pearl, 2013; Pearl, 2012).”
Legitimacy through CSR disclosures? The advantage outweighs the disadvantages (2016, background): “…the stimulus (“Extent of CSR Disclosure”) on the output measure (“Corporate Legitimacy”) and – at he same time – to take mediator variables (“Content Credibility”, “Perceived Persuasion Intent”, “Psychological Reactance”) nto account (consistent with Bollen & Pearl, 2013; pp. 316–318; Pearl, 2014).”