Linear Causal Modeling with Structural Equations

By S. Mulaik. 2009

273 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Physical and Theoretical Chemistry

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Veysel Yilmaz
2. J. D. de Winter
3. S. Maxwell
4. E. Arı
5. Dimitra Dodou
6. Joseph A. Maxwell

In Physical and Theoretical Chemistry

1. Veysel Yilmaz
2. J. D. de Winter
3. E. Arı
4. Dimitra Dodou
5. Joseph A. Maxwell

Citations in the corpus

• Bias in Cross-Sectional Analyses of Longitudinal Mediation: Partial and Complete Mediation Under an Autoregressive Model (2011, background): “…analyses to be accurate; (c) SEM has a long tradition in psychology and the other social sciences; (d) authors such as Pearl (2009) and Mulaik (2009) have shown that under specified conditions, SEM can provide a rigorous basis for causal inference, thus making it potentially…”
• A general approach to causal mediation analysis. (2010, unknown): “Although others have pointed to assumptions about residuals (Bullock, Green, & Ha, 2010; MacKinnon et al., 2002; Mulaik, 2009) and the consequences of omitted variables (James et al., 1982, pp. 71– 80), to our knowledge these scholars propose no formal sensitivity analysis about the identifying…”
• Factor recovery by principal axis factoring and maximum likelihood factor analysis as a function of factor pattern and sample size (2012, methodology): “Despite the existing formal mathematical framework and the available articles and textbooks elaborating on the properties of PAF and MLFA [1,5,10,21,28,37,40,46], there is little practical evidence regarding which factor analysis method should be preferred for different types of factor patterns and ”
• The effects of service quality, image, and customer satisfaction on customer complaints and loyalty in high-speed rail service in Turkey: a proposal of the structural equation model (2017, methodology): “Eachmethod is based on the minimization of the sum of squares of the errors obtained by subtracting the sample covariance matrix S from discrepancy functions of the estimation, that is, the covariance matrix (θ) (Mulaik 2009, 428).”
• The Importance of Qualitative Research for Causal Explanation in Education (2012, background): “This account is the basis for some of the current, most respected quantitative approaches to causal research (e.g., Mulaik, 2009, pp. 63-87; Murnane & Willett, 2010, pp. 26-38).2 Although logical positivism is no longer a viable philosophy of science, and the term “positivist” is often used far too…”