Structural Equation Modeling: Reviewing the Basics and Moving Forward

By Jodie B. Ullman. Journal of Personality Assessment, 2006

842 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Experimental and Cognitive Psychology, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/ba694010cd3154261b695675f7102d89ea0f248e

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In Computer Networks and Communications

In Experimental and Cognitive Psychology

In Management Science and Operations Research

Citations in the corpus

Linking Academic Entitlement and Student Incivility Using Latent Means Modeling (2013, methodology): “There is no universal cutoff value for this coefficient (Finney & DiStefano, 2013), but it has been suggested that utilizing maximum likelihood estimation with data having a standardized Mardia’s value greater than 3 could result in bias (Bentler & Wu, 2002; Ullman, 2006).”
The Development and Evaluation of the Academic Entitlement Questionnaire (2011, background): “However, some have suggested values greater than 3 paired with maximum likelihood (ML) estimation would produce inaccurate results (Bentler & Wu, 2002; Ullman, 2006).”
Multitrait index based on factor analysis and ideotype‐design: proposal and application on elephant grass breeding for bioenergy (2018, methodology): “In a CFA the researcher has a strong idea about the number of factors, the relations among the factors, and the relationship between the factors and measured traits; hence, the factor extraction and rotation are not part of CFA (Ullman, 2006).”
An empirical examination of consumer adoption of Internet of Things services: Network externalities and concern for information privacy perspectives (2016, neutral): “…(0.000)a 2.41 (0.000)a Bentler and Bonett (1980), Hair et al. (2006), Schumacker and Lomax (2004), Seyal, Rahman, and Rahim (2002), Scott (1994), Ullman (2006)GFI >0.8 0.85 0.87 AGFI >0.8 0.82 0.85 NFI >0.9 0.90 0.91 CFI >0.9 0.94 0.95 RMSEA <0.08 0.05 0.05 a For a larger sample size,…”
Common Beliefs and Reality About PLS (2014, background): “…SEM is not a single technique, but ‘‘a collection of statistical techniques that allow a set of relations between one or more independent variables (IVs), either continuous or discrete, and one or more dependent variables (DVs), either continuous or discrete, to be examined’’ (Ullman, 2006, p. 35).”