From: Imputation strategies for missing binary outcomes in cluster randomized trials

Imputation Level | Imputation strategies | Percentage of missingness | |||||
---|---|---|---|---|---|---|---|

5% | 10% | 15% | 20% | 30% | 50% | ||

Within cluster | Logistic regression | 0.949 | 0.902 | ||||

Propensity score | 0.947 | 0.899 | 0.850 | 0.801 | 0.706 | 0.524 | |

MCMC^{1}
| 0.948 | 0.901 | 0.854 | 0.806 | 0.714 | 0.535 | |

Across cluster | Propensity score | 0.949 | 0.903 | 0.853 | 0.805 | 0.713 | 0.529 |

Random-effects logistic regression | 0.951 | 0.908 | 0.859 | 0.808 | 0.717 | 0.538 | |

Fixed-effects logistic regression | 0.949 | 0.899 | 0.850 | 0.801 | 0.707 | 0.528 | |

Ignore cluster | Logistic regression | 0.947 | 0.895 | 0.844 | 0.793 | 0.695 | 0.508 |

Propensity score | 0.945 | 0.891 | 0.839 | 0.787 | 0.688 | 0.495 | |

MCMC^{1}
| 0.946 | 0.893 | 0.841 | 0.790 | 0.691 | 0.501 |