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 | 0.954 | 0.913 | Â | Â | Â | Â |
 | Propensity score | 0.953 | 0.910 | 0.865 | 0.820 | 0.730 | 0.549 |
 | MCMC1 | 0.954 | 0.913 | 0.869 | 0.825 | 0.737 | 0.561 |
Across cluster | Propensity score | 0.954 | 0.912 | 0.868 | 0.828 | 0.738 | 0.556 |
 | Random-effects logistic regression | 0.955 | 0.914 | 0.871 | 0.830 | 0.741 | 0.562 |
 | Fixed-effects logistic regression | 0.956 | 0.911 | 0.866 | 0.821 | 0.732 | 0.554 |
Ignore cluster | Logistic regression | 0.954 | 0.907 | 0.861 | 0.814 | 0.722 | 0.537 |
 | Propensity score | 0.952 | 0.902 | 0.854 | 0.804 | 0.707 | 0.512 |
 | MCMC1 | 0.953 | 0.906 | 0.859 | 0.811 | 0.717 | 0.530 |