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 | Â | Â | Â | Â |
 | Propensity score | 0.947 | 0.899 | 0.850 | 0.801 | 0.706 | 0.524 |
 | MCMC1 | 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 |
 | MCMC1 | 0.946 | 0.893 | 0.841 | 0.790 | 0.691 | 0.501 |