Missing data
death
REGRESSION, TRUNCATION, SENSITIVITY
Missing data on the composite safety outcome is likely to be minimal, so complete case analysis will be used. Missingness (frequency and percentage) will be reported for each combination of the components of the composite safety outcome. For the primary analysis, the composite safety outcome will be considered missing if (1) data on unscheduled readmission are missing and (2) the patient is not known to have experienced at least one of the two other components. This assumes that it would be known if a patient had restarted IV antibiotics or died. The potential influence of this assumption will be investigated by comparing estimates from best-case and worst-case imputation (“Sensitivity analyses” section).Missing data on IV antibiotic stopping time will lead to censoring at the patient’s last available clinical review. Patients with missing outcome data can therefore still be included in the Cox regression model, under the assumption that this censoring is non-informative. Truncation due to death would violate this assumption. The potential influence of this will be investigated in the survivor average causal effect (SACE) sensitivity analysis ( “Sensitivity analyses” section).