Description Details Author(s) References

A collection of functions for conducting meta-analysis using a structural equation modeling (SEM) approach via the 'OpenMx' and 'lavaan' packages. It also implements various procedures to perform meta-analytic structural equation modeling on the correlation and covariance matrices.

Package: | metaSEM |

Type: | Package |

Version: | 1.2.0 |

Date: | 2018-10-18 |

License: | GPL (>=2) |

LazyLoad: | yes |

Mike W.-L. Cheung <[email protected]>

Maintainer: Mike W.-L. Cheung <[email protected]>

Cheung, M. W.-L. (2008). A model for integrating fixed-, random-, and mixed-effects meta-analyses into structural equation modeling. *Psychological Methods*, **13**, 182-202.

Cheung, M. W.-L. (2009). Constructing approximate confidence intervals for parameters with structural equation models. *Structural Equation Modeling*, **16**, 267-294.

Cheung, M. W.-L. (2010). Fixed-effects meta-analyses as multiple-group structural equation models. *Structural Equation Modeling*, **17**, 481-509.

Cheung, M. W.-L. (2013). Implementing restricted maximum likelihood estimation in structural equation models. *Structural Equation Modeling*, **20**, 157-167.

Cheung, M. W.-L. (2013). Multivariate meta-analysis as structural equation models. *Structural Equation Modeling*, **20**, 429-454.

Cheung, M. W.-L. (2014). Modeling dependent effect sizes with three-level meta-analyses: A structural equation modeling approach. *Psychological Methods*, **19**, 211-229.

Cheung, M. W.-L. (2014). Fixed- and random-effects meta-analytic structural equation modeling: Examples and analyses in R. *Behavior Research Methods*, **46**, 29-40.

Cheung, M. W.-L. (2015). metaSEM: An R package for meta-analysis using structural equation modeling. *Frontiers in Psychology*, **5**, 1521.

Cheung, M. W.-L. (2015). *Meta-Analysis: A Structural Equation Modeling Approach*. Chichester, West Sussex: John Wiley & Sons, Inc.

Cheung, M. W.-L. (2018). Issues in solving the problem of effect size
heterogeneity in meta-analytic structural equation modeling: A
commentary and simulation study on Yu, Downes, Carter, and O'Boyle (2016). *Journal of Applied Psychology*, **103**, 787-803.

Cheung, M. W.-L. (2018). Computing multivariate effect sizes and their sampling covariance matrices with structural equation modeling: Theory, examples, and computer simulations. *Frontiers in Psychology*, **9**(1387). https://doi.org/10.3389/fpsyg.2018.01387

Cheung, M. W.-L. (2018). Some reflections on combining meta-analysis and structural equation modeling. *Research Synthesis Methods*, **0**(0).

Cheung, M. W.-L., & Chan, W. (2004). Testing dependent correlation coefficients via structural equation modeling. *Organizational Research Methods*, **7**, 206-223.

Cheung, M. W.-L., & Chan, W. (2005). Meta-analytic structural equation modeling: A two-stage approach. *Psychological Methods*, **10**, 40-64.

Cheung, M. W.-L., & Chan, W. (2009). A two-stage approach to synthesizing covariance matrices in meta-analytic structural equation modeling. *Structural Equation Modeling*, **16**, 28-53.

Cheung, M. W.-L., & Cheung, S.-F. (2016). Random-effects models for meta-analytic structural equation modeling: Review, issues, and illustrations. *Research Synthesis Methods*, **7**, 140-155.

Jak, S, & Cheung, M. W.-L. (2018). Testing moderator hypotheses in meta-analytic structural equation modeling using subgroup analysis. *Behavior Research Methods*, **50**, 1359-1373.

metaSEM documentation built on Oct. 18, 2018, 9:03 a.m.

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