Quality of Life Research

, Volume 1, Issue 3, pp 219–224 | Cite as

Statistical analysis of longitudinal quality of life data with missing measurements

  • A. H. Zwinderman
Statistical Review

Abstract

The statistical analysis of longitudinal quality of life data in the presence of missing data is discussed. In cancer trials missing data are generated due to the fact that patients die, drop out, or are censored. These missing data are problematic in the monitoring of the quality of life during the trial. However, by means of assuming that the cause of the missing data lies in the observed history of the patients and not in their unobserved future, the missing data are ignorable. Consequently, all available data can be used to estimate quality of life change patterns with time. The computations that are required are illustrated with real quality of life data and three commonly used computer packages for statistical analysis.

Key words

Longitudinal analysis missing data quality of life 

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Copyright information

© Rapid Communications of Oxford Ltd 1992

Authors and Affiliations

  • A. H. Zwinderman
    • 1
  1. 1.Department of Medical StatisticsUniversity of LeidenLeidenThe Netherlands

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