BACKGROUND: There are a variety of techniques to handle missing data, such as removing
observations with missing data from the analyses or estimating the missing values using
various imputation algorithms. Dropping subjects from standard regression models and
analyzing only completers, however, may bias results from the true value of reality.
Likewise,'last-observation-carried-forward'may not be an appropriate technique for studies
measuring a particular variable over time. METHODS: This dataset was part of a larger …