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tion, clustering, and use of existing data must be considered. These design elements are typically
found individually in current accuracy assessment practice, but greater efficiency may be gained
by more innovatively combining their strengths. To ensure scientific credibility, sampling designs
for accuracy assessment should satisfy the criteria defining a probability sample. This requirement
places additional burden on how various design elements are integrated. When exploring alternative
design options, the apparently simple answers may not be as straightforward as they first appear.
Combining basic design structures such as strata and clusters to enhance efficiency has some
significant complicating factors, and use of existing data for accuracy assessment has associated
hidden costs even if the data are free
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