Potential impact of missing outcome data on treatment effects in systematic reviews: imputation study.

This would account for factors such as percentage of missing data in each study arm, the ratio of missing data to event rate for each study arm (ie, the higher the ratio, the larger the change), fragility of statistical significance (ie, borderline significance), the magnitude of the effect estimate (ie, the larger the effect estimate, the smaller the change), and the duration of follow-up (ie, the longer the duration of follow-up, the higher the percentage of missing data).

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