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Table 6 MNAR 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

0.031 (0.027)

0.947

+0.001

MI: wt, hb, age, para

4,989

0.031 (0.028)

0.960

+0.001

MI: hb, age, para

4,988

0.030 (0.027)

0.961

0.000

MI: hb, age, para, group

4,992

0.032 (0.028)

0.950

+0.002

MI: wt, hb, age, para, group

4,992

0.032 (0.028)

0.955

+0.002

15 % of outcomes missing

    

Complete Case

5,000

0.035 (0.030)

0.951

+0.005

MI: wt, hb, age, para

4,985

0.029 (0.031)

0.981

0.000

MI: hb, age, para

4,990

0.030 (0.031)

0.981

-0.001

MI: hb, age, para, group

4,991

0.035 (0.032)

0.960

+0.005

MI: wt, hb, age, para, group

4,989

0.036 (0.032)

0.961

+0.006

30 % of outcomes missing

    

CC

5,000

0.042 (0.036)

0.950

+0.012

MI: wt, hb, age, para

4,982

0.030 (0.038)

0.992

0.000

MI: hb, age, para

4,991

0.030 (0.037)

0.991

0.000

MI: hb, age, para, group

4,988

0.043 (0.040)

0.965

+0.013

MI: wt, hb, age, para, group

4,991

0.043 (0.041)

0.965

+0.013

  1. *Number of data sets for which convergent analysis was achieved