P10
Imputation of Longitudinal Incomplete Data in Clinical Trials
Naum M. Khutoryansky, Novo Nordisk Pharmaceuticals, Inc.

In longitudinal clinical trials missing data are mostly related to dropouts. Some dropouts appear completely at random. The source for other dropouts is withdrawal from trials due to lack of efficacy. For the latter case the analyses of the actual observed data and completers can produce bias. One of the approaches to comply with the intent-to-treat principle is the imputation of incomplete data. This paper deals with the incremental method of imputation (introduced in a paper in the PharmaSUG 2001 conferen ce proceedings). Comparison is done between the incremental method results and the SAS MIXED procedure results on simulated data.