Abstract #300830

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JSM 2002 Abstract #300830
Activity Number: 82
Type: Contributed
Date/Time: Monday, August 12, 2002 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section*
Abstract - #300830
Title: Incremental Methods of Imputation in Longitudinal Clinical Trials
Author(s): Naum Khutoryansky*+ and Michael Chernick
Affiliation(s): Novo Nordisk Pharmaceuticals, Inc and Novo Nordisk Pharmaceuticals Inc
Address: 100 College Rd. West, Princeton, New Jersey, 08540, USA
Keywords: clinical trials ; longitudinal data ; missing data ; imputation
Abstract:

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 methods of imputation applied to incomplete longitudinal data sets with MAR drop-outs. Comparison is done between the incremental methods and some other imputation methods (including the last observation carried-forward method and linear mixed-models method) on simulated longitudinal data. The data sets are simulated to resemble time behavior of the HbA1c and fasting plasma glucose in diabetes clinical trials.

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Revised March 2002