z-logo
open-access-imgOpen Access
Outcome-Dependent Sampling
Author(s) -
Haibo Zhou,
Jianwei Chen,
Tiina H. Rissanen,
Susan Korrick,
Howard Hu,
Jukka T. Salonen,
Matthew P. Longnecker
Publication year - 2007
Publication title -
epidemiology
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.901
H-Index - 173
eISSN - 1531-5487
pISSN - 1044-3983
DOI - 10.1097/ede.0b013e31806462d3
Subject(s) - outcome (game theory) , medicine , statistics , mathematics , mathematical economics
To characterize the relation between an exposure and a continuous outcome, the sampling of subjects can be done much as it is in a case-control study, such that the sample is enriched with subjects who are especially informative. In an outcome-dependent sampling design, observations made on a judiciously chosen subset of the base population can provide nearly the same statistical efficiency as observing the entire base population. Reaping the benefits of such sampling, however, requires use of an analysis that accounts for the outcome-dependent sampling. In this report, we examine the statistical efficiency of a plain random sample analyzed with standard methods, compared with that of data collected with outcome-dependent sampling and analyzed by either of 2 appropriate methods. In addition, 3 real datasets were analyzed using an outcome-dependent sampling approach. The results demonstrate the improved statistical efficiency obtained by using an outcome-dependent sampling, and its applicability in a wide range of settings. This design, coupled with an appropriate analysis, offers a cost-efficient approach to studying the determinants of a continuous outcome.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here