The Causal Foundations of Structural Equation Modeling

By Judea Pearl. 2012

345 citations recorded by the source corpus.

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Citations in the corpus

Counterfactuals uncover the modular structure of deep generative models (2018, methodology): “Then for a given value z of the latent variables, called unit , the unit-level counterfactual is the output of M v 0 , This is essentially the deﬁnition in [Pearl, 2014], with notations adapted to the context of CGMs.”
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).”
Covariance-Based Structural Equation Modeling in the Journal of Advertising: Review and Recommendations (2017, background): “Pearl (2009, 2010, 2012, 2014) provides a comprehensive review of causality and SEM, and points out that the greater accessibility to statistical techniques coincides with users who may lack a fundamental understanding of key principles.”
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).”
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).”
Guidelines for a graph-theoretic implementation of structural equation modeling (2012, background): “Only the combination of statistical relations and causal assumptions can yield causal inferences (Pearl 2012).”
EIGHT MYTHS ABOUT CAUSALITY AND STRUCTURAL EQUATION MODELS (2013, methodology): “The natural effects, on the other hand, require an additional assumption that "2 and "3 be independent conditional on covariates that are unaffected by X (Pearl 2001, 2012b; Chap.”
Do cooperative enterprises create social trust? (2012, neutral): “…of our arguments and through the effectiveness of empirical tests, to demonstrate the existence of a causal connection between the spread of cooperatives and the development of trust, we hasten to add that we have not been able to demonstrate causation in a definitive way (Wright 1934; Pearl 2012).”
Applications of structural equation modeling (SEM) in ecological studies: an updated review (2016, methodology): “The original causal foundation of SEM was based on a hypothesis test (Pearl 2003, 2009, 2012; Bareinboim and Pearl 2015).”
Enhancing Rigor in Quantitative Entrepreneurship Research (2019, methodology): “Furthermore, 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; P”
TRYGVE HAAVELMO AND THE EMERGENCE OF CAUSAL CALCULUS (2014, neutral): “2 (see, for example, Greenland and Pearl, 2011; Kyono, 2010; or Pearl, 2010a, 2010b, 2012a).”
Empathetic Leadership: How Leader Emotional Support and Understanding Influences Follower Performance (2018, background): “The model presents a causal statement in line with Pearl (2012, 2014), Bollen and Pearl’s (2013), and Goldthorpe’s (2001) suggestions for establishing causal linkages between constructs.”
Causes of Effects and Effects of Causes (2015, methodology): “Portions of this paper are based on Pearl (2000a, 2011, 2012).”