Table 6.

Covariate adjustment and missing data treatment (N=62)

Characteristic	Frequency (%)
If covariates were used in the randomization, did primary outcome analysis adjust for those covariates? (N=38)
Yes, for all relevant covariates	14 (36.8%)
Yes, but not for all relevant covariates	4 (10.5%)
No	18 (47.4%)
Uncleara	2 (3.2%)
Does the trial have missing outcomes or attrition for the primary outcome?
Yes	59 (95.2%)
No	2 (3.2%)
Unclear	1 (1.6%)
Method used to account for missing data in the primary analysis of the primary outcome (N=59)
None	34 (57.6%)
Regression adjustment for covariates stated to be associated with missingness	6 (9.7%)
Single imputation	9 (14.5%)
Multiple imputation	9 (14.5%)
Otherb	1 (1.7%)
Method used to account for missing data in sensitivity analyses of the primary outcome (N=59)
None	52 (88.1%)
Regression adjustment for covariates stated to be associated with missingness	3 (5.1%)
Single imputation	2 (3.4%)
Multiple imputation	1 (1.7%)
Otherc	1 (1.7%)
Any method used to account for missing data in primary or sensitivity analyses for the primary outcome?
Yes	27 (45.8%)
No	32 (54.2%)
Did the trial report a statistically significant effect for the primary outcome(s)?
Yes	30 (48.4%)
No	29 (46.8%)
Mixed resultsd	3 (4.8%)

^aOne trial presented both adjusted and unadjusted analyses without clearly stating the primary analysis; one trial used stratification but did not define the stratification variables

^bPrimary outcome assessed in “modified intent to treat population” consisting only of those residents with available data at 8 months

^cSingle imputation for primary analysis followed by complete case analysis as sensitivity analysis

^dOne trial did not present results for the overall outcome score, but only for the individual components; one three-arm trial had two co-primary outcomes with mixed results; one trial had three co-primary outcomes with mixed results