Publisher: Chapman and Hall/CRC
Year of Publication: 2016
Author(s) : Craig Mallinckrodt, Ilya Lipkovich
Missing data in longitudinal clinical trials has justifiably been the target of considerable research. However, missing data is just one of the many considerations in the analysis of longitudinal data, and focus on the data we don’t have should not distract from focus on the data we do have. The statistical theory relevant to analyses of longitudinal data is extensive. However, the greatest difficulty may not be in knowing the theory, but rather in putting the theory into useful practice. Therefore, this book focuses on the most relevant and current theory for the common issues faced in planning and implementing analyses for longitudinal trials.
Emphasizes how to analyze longitudinal data that may include missing data
Focuses on the most relevant and current theory for the common issues faced in planning and implementing analyses for longitudinal trials
Emphasizes bringing that theory into routine use in a practical and efficient manner via extensive examples with realistic data and the programming code to implement the analyses.
Uses a holistic approach that considers the interactions between estimands (what is to be estimated), trial design, and trial analyses, along with the focus on practical implementation that sets this text apart from existing texts.