Abstract:
In clinical trials with a long period of time between randomization and the primary assessment of the
patient, the same assessments are often undertaken at intermediate times. When an interim analysis is
conducted, in addition to the patients who have completed the primary assessment, there will be those
who have till then undergone only intermediate assessments. The efficiency of the interim analysis can be
increased by the inclusion of data from these additional patients. This paper compares four methods of
increasing information based on model-free estimates of transition probabilities to incorporate intermediate
assessments from patients who have not completed the trial. It is assumed that the observations are binary
and that there is one intermediate assessment. The methods are the score and Wald approaches, each with
the log-odds ratio and probability difference parameterizations. Simulations show that all four approaches
have good properties in moderate to large sample sizes
