Abstract

Tests for correlations between sample size and taxonomic relative abundance are commonly used in zooarchaeological analyses to determine whether observed trends in relative abundance might simply be the result of sampling error. Monte Carlo simulations designed to evaluate the utility of this method indicate that it is inadequate as a means of detecting errors resulting from the incorporation of small samples in an analysis. Among simulated sets of sample assemblages, significant correlatoins between sample size and relative abundance are distributed randomly with respect to whether or not Type II errors concerning trends in relative abundance are present, and are underrepresented in cases in which Type I errors are present. This is because the conditions that are most conducive to correlations between sample size and relative abundance are quite different from the conditions that will lead to erroneous conclusions about the presence or absence of a trend in relative abundance. An alternative chi-square-based statistical method for evaluating trends in sample relative abundance, Cochran's test of linear trend, results in lower rates of both Type I and Type II errors than is the case with previously used correlation-based methods.

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