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Table 4 MAR 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 the 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 4,982 0.027 (0.027) 0.951 -0.003
MI: hb, age, para 4,988 0.027 (0.027) 0.955 -0.003
MI: hb, age, para, group 4,989 0.029 (0.027) 0.946 -0.001
MI: wt, hb, age, para, group 4,986 0.029 (0.027) 0.947 -0.001
15 % of outcomes missing     
CC 5000 0.030 (0.028) 0.942 0.000
MI: wt, hb, age, para 4969 0.025 (0.029) 0.970 -0.005
MI: hb, age, para 4983 0.025 (0.029) 0.963 -0.005
MI: hb, age, para, group 4981 0.030 (0.030) 0.965 0.000
MI: wt, hb, age, para, group 4982 0.030 (0.030) 0.965 0.000
30 % of outcomes missing     
CC 5,000 0.030 (0.030) 0.937 0.000
MI: wt, hb, age, para 4,893 0.020 (0.033) 0.970 -0.010
MI: hb, age, para 4,949 0.021 (0.033) 0.98 -0.009
MI: hb, age, para, group 4,945 0.030 (0.037) 0.967 0.000
MI: wt, hb, age, para, group 4,938 0.031 (0.037) 0.971 +0.001
  1. *Number of data sets for which convergent analysis was achieved
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