American Journal of Epidemiology, Vol 152, Issue 8 771-779, Copyright © 2000 by Oxford University Press
EB Hook and RR Regal
The authors used "internal validity analysis" to evaluate the performance
of various capture-recapture methods. Data from studies with five
overlapping, incomplete lists generated subgroups whose known sizes were
compared with estimates derived from various four-source capture-recapture
analyses. In 15 data sets unanalyzed previously (five subgroups of each of
three new studies), the authors observed a trend toward mean
underestimation of the known population size by 16-25%. (Coverage of the
90% confidence intervals associated with the method found to be optimal was
acceptable (13/15), despite the downward bias.) The authors conjectured
that (with the obvious exception of geographically disparate lists) most
data sets used by epidemiologists tend to have a net positive dependence;
that is, cases captured by one source are more likely to be captured by
some other available source than are cases selected randomly from the
population, and this trend results in a bias toward underestimation.
Attempts to ensure that the underlying assumptions of the methods are met,
such as minimizing (or adjusting adequately) for the possibility of loss
due to death or migration, as was undertaken in one exceptional study,
appear likely to improve the behavior of these methods.
Accuracy of alternative approaches to capture-recapture estimates of disease frequency: internal validity analysis of data from five sources [In Process Citation]
School of Public Health, University of California, Berkeley 94720-7360, USA. ebhook@socrates.berkeley.edu
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