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Table 5 MCAR and efficacy rate 98 % versus 95 % (RD 0.030): estimated efficacy differences, coverage and bias for 5 %, 15 % and 30 % averages of number of simulated data sets that converged of 5000 data sets, 50 imputations

From: Is using multiple imputation better than complete case analysis for estimating a prevalence (risk) difference in randomized controlled trials when binary outcome observations are missing?

Model No. of data sets* RD (RMSE) Coverage Bias
All outcomes recorded: 5,000 0.030 (0.026) 0.939 0.000
5 % of outcomes missing     
CC 5,000 0.030 (0.026) 0.940 0.000
MI: wt, hb, age, para 4,977 0.028 (0.027) 0.948 -0.002
MI: hb, age, para 4,982 0.028 (0.027) 0.957 -0.002
MI: hb, age, para, group 4,992 0.030 (0.027) 0.953 0.000
MI: wt, hb, age, para, group 4,988 0.030 (0.027) 0.951 0.000
15 % of outcomes missing     
CC 5,000 0.030 (0.028) 0.944 0.000
MI: wt, hb, age, para 4,962 0.026 (0.029) 0.970 -0.004
MI: hb, age, para 4,969 0.025 (0.029) 0.970 -0.005
MI: hb, age, para, group 4,984 0.031 (0.030) 0.957 +0.001
MI: wt, hb, age, para, group 4,972 0.031 (0.030) 0.961 +0.001
30 % of outcomes missing     
CC 5,000 0.030 (0.030) 0.940 0.000
MI: wt, hb, age, para 4,896 0.021 (0.033) 0.969 -0.009
MI: hb, age, para 4,937 0.021 (0.033) 0.978 -0.009
MI: hb, age, para, group 4,948 0.031 (0.037) 0.971 +0.001
MI: wt, hb, age, para, group 4933 0.031 (0.038) 0.967 +0.001
  1. *Number of data sets for which convergent analysis was achieved