Send to

Choose Destination
See comment in PubMed Commons below
Med Decis Making. 1997 Oct-Dec;17(4):431-8.

Optimizing sampling strategies for estimating quality-adjusted life years.

Author information

  • 1Department of Medicine, University of Washington Medical Center, Seattle, USA.


Accurate estimation of quality of life is critical to cost-effectiveness analysis. Nevertheless, development of sampling algorithms to maximize the accuracy and efficiency of estimated quality of life has received little consideration to date. This paper presents a method to optimize sampling strategies for estimating quality-adjusted life years. In particular, the authors address the questions of when to sample and how many observations to sample at each sampling time, assuming realistically that the sample variance of quality of life is not constant over time. The method is particularly useful for the design problems researchers face when time or research budget constraints limit the number of individuals that can be surveyed to estimate quality of life. The article focuses on cross-sectional sampling. The method proposed requires some knowledge of survival in the population of interest, the approximate variances in utilities at various points along the curve, and the general shape of the quality-adjusted survival curve. Such data are frequently available from disease registries, the literature, or previous studies.

[PubMed - indexed for MEDLINE]

LinkOut - more resources

Full Text Sources

Other Literature Sources

PubMed Commons home

PubMed Commons

How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Atypon
    Loading ...
    Support Center