O'Reilly logo

Preventing and Treating Missing Data in Longitudinal Clinical Trials by Craig Mallinckrodt

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

7 Models and Modeling Considerations

7.1 Introduction

The data from longitudinal clinical trials may be as varied as the trials themselves. Verbeke and Molenberghs (2000) provided a detailed and broad review of longitudinal data analyses and Molenberghs and Kenward (2007) provided a similar review specific to clinical trial data.

Given the variety of scenarios that may be encountered in longitudinal clinical trials, no universally best model or modeling approach exists. This implies that the analysis must be tailored to the situation at hand. To an extent, characteristics of the data are driven by the design of the study, and an appropriate analysis follows logically from the design.

Four important characteristics to consider when specifying analyses ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required