Statistical analysis of longitudinal quality of life data with missing measurements
- A. H. Zwinderman
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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.
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- Statistical analysis of longitudinal quality of life data with missing measurements
Quality of Life Research
Volume 1, Issue 3 , pp 219-224
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers
- Additional Links
- Longitudinal analysis
- missing data
- quality of life
- Industry Sectors
- A. H. Zwinderman (1)
- Author Affiliations
- 1. Department of Medical Statistics, University of Leiden, PO Box 9604, 2300 RC, Leiden, The Netherlands