Source: Ann. Appl. Stat.
Volume 5, Number 4
Pooling specimens, a well-accepted sampling strategy in biomedical
research, can be applied to reduce the cost of studying
biomarkers. Even if the cost of a single assay is not a major
restriction in evaluating biomarkers, pooling can be a powerful
design that increases the efficiency of estimation based on data
that is censored due to an instrument’s lower limit of detection
(LLOD). However, there are situations when the pooling design
strongly aggravates the detection limit problem. To combine the
benefits of pooled assays and individual assays, hybrid designs
that involve taking a sample of both pooled and individual
specimens have been proposed. We examine the efficiency of these
hybrid designs in estimating parameters of two systems subject
to a LLOD: (1) normally distributed biomarker with normally
distributed measurement error and pooling error; (2) Gamma
distributed biomarker with double exponentially distributed
measurement error and pooling error. Three-assay design and
two-assay design with replicates are applied to estimate the
measurement and pooling error. The Maximum likelihood method is
used to estimate the parameters. We found that the simple
one-pool design, where all assays but one are random individuals
and a single pooled assay includes the remaining specimens,
under plausible conditions, is very efficient and can be
recommended for practical use.
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