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Table 4 Reporting of methods for controlled MI

From: A review of the use of controlled multiple imputation in randomised controlled trials with missing outcome data

Controlled MI feature

n

(N = 16ª)

%

Type of primary outcome

 Binary

4

25%

 Continuous

9

56%

 Time-to-event

3

19%

Type of controlled MI

 Delta-based MI

9

56%

 Reference based MI

7

44%

Method of delta-based MI (N = 9)

 MICEe

2

22%

 MVN imputation (non-monotone missing patterns) and regression MI model (monotone patterns)

1

11%

 Kaplan-Meier MI (KMMI)

2b

22%

 ANCOVA MI

1

11%

 Cox model MI

1

11%

 Not stated

3

27%

Method of reference-based MI (N = 7)

 MCMC or random draws from a normal distribution with mean equal to subject’s own baseline valuef

1

14%

 Linear MMRM

2

29%

 Kaplan-Meier MI (KMMI)

1

14%

 Not stated

3

43%

Specified variables in imputation model

9

56%

 Imputation model incl. All variables in analysis model only

5

31%

 Imputation model incl. All variables in analysis model + auxiliary variables

3

19%

 Imputation model did not include all variables in analysis modelg

1

6%

Did not specify variables in imputation model

7

44%

 Imputation model incl. All variables in analysis model + auxiliary variables

2

13%

Reported the number of imputations

13

81%

No. of imputations

 5

2

13%

 20

1

6%

 100

6

38%

 1000

4

25%

Not stated

3

19%

Specific procedure/command(s) (software) for implementing MI

 Proc MI and Proc MIANALYZE (SAS)

2

13%

 Proc MIXED and Proc MIANALYZE (SAS)

2

13%

 Not stated

12

75%

Rubin’s rules used for inference

 Yesh

9

56%

 Noc

1

6%

 Not stated

6

38%

Analysis status

 Primary

2

13%

 Sensitivity

14

87%

No. scenarios used in sensitivity analysisd

Median

Range

 Median (range)

3

(1–48)

Performed diagnostic check of imputations

0

0%

  1. ª Denominator for variables 16 unless otherwise indicated. bOne trial used both KKMI and Cox model MI in two separate sensitivity analyses. cOne trial reported using a modified version of Rubin’s rules, “the overall average estimated event rate difference and average estimated variance” (did not incorporate any between imputation variability in the variance calculation). dN = 13. Not clear for 1/14 trials using controlled MI in sensitivity analysis. eNo further details available on types of models utilised within MICE. fMissing data during the on-treatment period were imputed “using the MI SAS procedure (using Markov Chain Monte Carlo)” and values missing values during the post-treatment period were “multiply imputed using random draws from a normal distribution where the mean was equal to subject’s own baseline value.” gOne trial did not include all variables in analysis model and included auxiliary variables in the imputation model. h Explicitly stated (n = 5) or inferable from specified software or reference (n = 4). Percentages are rounded to 0 decimal places so may not sum exactly to 100%