Abstract #300997

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JSM 2002 Abstract #300997
Activity Number: 351
Type: Topic Contributed
Date/Time: Wednesday, August 14, 2002 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract - #300997
Title: Modeling Incomplete Observations of Quality of Life
Author(s): Michel Chavance*+
Affiliation(s): INSERM U472
Address: 16 Ave. P. Vaillant-Couturier, Villejuif, International, F94807, FRANCE
Keywords: Missing data ; Quality of life ; multiple imputation ; MCMC methods
Abstract:

Quality of life (QOL) observations may be incomplete, either because some items, used to measure QOL, are missing and only a partial measure is available or because some scheduled measures of QOL were not performed at all. This presentation is focused on the first situation. MCMC methods and multiple imputation of the global measure using predictive models of the missing answers can be used, either assuming that data are missing at random (i.e., missingness depends only on the observed items) or assuming that data are not missing at random (i.e., missingness depends also on the value of the missing item). Thus, the investigator can study the sensitivity of the results to the assumptions made on missingness. Both approaches are compared to the usual simple imputation of a single measure proportional to the partial measure available.

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