Abstract
Neutral models are foundational in the archaeological study of cultural transmission. Applications have assumed that archaeological data represent synchronic samples, despite the accretional nature of the archaeological record. Using numerical simulations, I document the circumstances under which time-averaging alters the distribution of model predictions. Richness is inflated in long-duration assemblages, and evenness is “flattened” compared to unaveraged samples. Tests of neutrality, employed to di erentiate between biased and unbiased models, su er serious problems with Type I error under time-averaging. Estimation of populationlevel innovation rates, which feature in many archaeological applications, are biased even without time averaging, but have sharply increased bias given longer assemblage durations. Finally, the time scale over which time averaging alters predictions is determined by the mean trait lifetime, providing a way to evaluate the impact of these e ects upon archaeological samples.
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