SEM and CFA |

Model Complexity or/and number of model parameters estimated |

Analyses in which all outcome variables are continuous |

Normally distributed data, and there are no |

Linear effects existing in data |

Existing interactions between data |

Estimation method |

The lower the reliability of the scores the higher the required sample size |

Is it a latent variable models or observed variable model? |

Less precise data requires larger samples |

Missing data require larger sample sizes |

CFA in particular |

Low number of indicators for the constructs of interest per factor requires larger samples |

Lower number of indicators per factor requires larger samples |

Indicators that covary highly with multiple factors require larger samples |

If the number of factors is high a larger sample is needed |

If covariances between factors are low a larger sample is needed |