TEACHER'S CORNER: Structural Equation Modeling With the sem Package in R

By John Fox. 2006

495 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/71cfe21ddea073f72e6458412730edeca484658c

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In Computer Networks and Communications

In Experimental and Cognitive Psychology

In Management Science and Operations Research

Citations in the corpus

Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods (2015, methodology): “The allele score method was performed using the tsls command in the sem package [38]; the summary statistic method was calculated ‘by hand’, and the likelihood-based method was implemented in a maximum likelihood framework, using the optim command for numerical optimization.”
The Components of the Simple View of Reading: A Confirmatory Factor Analysis (2012, methodology): “Analyses were performed using the sem package (Fox, 2006) in R (R Development Core Team, 2005), after renormalizing each variable over the entire sample.”
Qgraph: Network visualizations of relationships in psychometric data (2012, methodology): “However, the techniques in the package have also proved useful as a more general tool for visualizing data, and include methods to visualize output from several psychometric packages like sem (Fox 2006; Fox et al. 2012) and lavaan (Rosseel 2012).”
semPLS: Structural Equation Modeling Using Partial Least Squares (2012, methodology): “Exporting plsm objects for use with sem If we are interested in a covariance-based estimation of the path coefficients, we can for example use the sem package (Fox 2006; Fox et al. 2012).”
Undergraduate Attitudes Toward the Elderly: The Role of Knowledge, Contact and Aging Anxiety (2008, methodology): “…¼ c0 þ c1Knowledgeþ c2WorkContactþ c3HomeContact þ c4Ageismþ u2 ð2Þ The model was estimated with full information maximum likelihood (FIML) estimators using the sem package in R (Fox, 2006). b4 and c4 were found to be individually and jointly insignificantly different from zero at the a¼ .10 level.”
Single-Case Experimental Designs: A Systematic Review of Published Research and Current Standards (2012, methodology): “Fox J. TEACHER’S CORNER: Structural equation modeling with the sem package in R. Structural Equation Modeling: A Multidisciplinary Journal.”
Attitudes towards road pricing and environmental taxation among US and UK students (2013, methodology): “Among several available software packages that allow SEM fitting we chose the R SEM package (Fox, 2006).”
lavaan: An R Package for Structural Equation Modeling (2012, methodology): “The sem package, developed by John Fox, has been around since 2001 (Fox, Nie, and Byrnes 2012; Fox 2006) and for a long time, it was the only package for SEM in the R environment.”
Multiplicity Control in Structural Equation Modeling: Incorporating Parameter Dependencies (2013, methodology): “The simulation was conducted using R (R Development Core Team, 2010) employing the sem package (Fox, 2006).”
Ensuring Positiveness of the Scaled Difference Chi-square Test Statistic (2010, background): “A wide variety of computer programs can carry out analyses for a general class of structural equation models, including AMOS (SPSS, 2008), CALIS (SAS, 2008), EQS (Bentler, 2008), LISREL (Jöreskog & Sörbom, 1999), Mplus (Muthén & Muthén, 2007), Mx (Neale, 1997), and sem in R (Fox, 2006).”
Climate‐driven increases in storm frequency simplify kelp forest food webs (2011, methodology): “All models were fit using the sem package in R (Fox, 2006).”
Functional and phylogenetic diversity as predictors of biodiversity--ecosystem-function relationships. (2011, methodology): “SEMs were implemented using the R package sem (Fox 2006).”
lavaan.survey: An R Package for Complex Survey Analysis of Structural Equation Models (2014, background): “None of the open-source SEM packages, sem (Fox 2006; Fox, Nie, and Byrnes 2012), openMx (Boker et al. 2011), and lavaan (Rosseel 2012), directly implement complex survey adjustments.”