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Abstract Details
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Activity Number:
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641
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Type:
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Invited
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Date/Time:
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Thursday, August 4, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #300084 |
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Title:
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Examples of Changes to the Analyses of Vaccine Studies Due to the NRC Report on the Handling of Missing Data
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Author(s):
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Robert D. Small*+ and Ayca Ozol-Godfrey
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Companies:
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Sanofi-Pasteur and Sanofi-Pasteur
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Address:
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Discovery Drive, Swiftwater, PA, 18370, USA
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Keywords:
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Missing data ;
Assay ;
Multiple Imputation
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Abstract:
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Immunological assays usually have a lower limit of sensitivity which is known. When an assay produces a result below this limit, it has been a common practice to replace the missing values by a single value such as the limit itself or some fraction of the limit. It happens that for some vaccines and diseases, 25% or more of the data can be missing in this way. In this paper the naïve single imputation is replaced with an MI approach taking advantage of correlations between the missing quantity and other characteristics to produce an effective imputation model that modifies the estimates of error in evaluating the immunological effect of vaccines. This approach can be used in a number of different kinds of vaccine trials. The methods will be demonstrated on some H1N1 data.
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