### Abstract

We simulated Bayesian CFA models to investigate the power of PPP to detect model misspecification by manipulating sample size, strongly and weakly informative priors for nontarget parameters, degree of misspecification, and whether data were generated and analyzed as normal or ordinal. Rejection rates indicate that PPP lacks power to reject an inappropriate model unless priors are unrealistically restrictive (essentially equivalent to fixing nontarget parameters to zero) and both sample size and misspecification are quite large. We suggest researchers evaluate global fit without priors for nontarget parameters, then search for neglected parameters if PPP indicates poor fit.

Original language | English |
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Title of host publication | Quantitative Psychology - 83rd Annual Meeting of the Psychometric Society, 2018 |

Editors | Rianne Janssen, Steven Culpepper, Marie Wiberg, Dylan Molenaar, Jorge González |

Publisher | Springer New York LLC |

Pages | 255-263 |

Number of pages | 9 |

ISBN (Print) | 9783030013097 |

DOIs | |

State | Published - 2019 |

Event | 83rd Annual meeting of the Psychometric Society, 2018 - New York, United States Duration: Jul 9 2018 → Jul 13 2018 |

### Publication series

Name | Springer Proceedings in Mathematics and Statistics |
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Volume | 265 |

ISSN (Print) | 2194-1009 |

ISSN (Electronic) | 2194-1017 |

### Conference

Conference | 83rd Annual meeting of the Psychometric Society, 2018 |
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Country | United States |

City | New York |

Period | 07/9/18 → 07/13/18 |

### Keywords

- Bayesian inference
- Confirmatory factor analysis
- Model evaluation
- Model modification
- Structural equation modeling

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## Cite this

*Quantitative Psychology - 83rd Annual Meeting of the Psychometric Society, 2018*(pp. 255-263). (Springer Proceedings in Mathematics and Statistics; Vol. 265). Springer New York LLC. https://doi.org/10.1007/978-3-030-01310-3_23