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Missing data were imputed using a last value carried forward strategy.
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Time-varying covariates used a last value carried forward approach until the time a new measurement was obtained.
For time dependent variables we used a last value carried forward approach, within each imputation.
In sensitivity analyses, missing outcome data were imputed using a last-value carried forward approach.
Missing data were estimated using a last-value-carried-forward approach in patients completing the study.
Because these are self-reported data collected every 3 months, we will use a "last-value carried forward" approach to handle missing data as our primary analytic strategy.
Because these are self-reported data collected on a semi-annual basis, we will use a "last-value carried forward" approach to handle missing data as our primary analytic strategy.
For mean change in DAS28-CRP scores, HAQ-DI scores and ACR core component scores, missing values were imputed using a last observation carried forward analysis.
Response and remission rates were analyzed using a logistic regression model with the treatment group and baseline MADRS score as explanatory variables; missing values were imputed using a last observation carried forward (LOCF) approach.
The impact of missing data was investigated using the last value carried forward (LVCF) imputation method, assuming that a participant's scores remained constant until the next response was observed.
Statistical analysis based on the intention-to-treat principle while using the last value technique.
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