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  1. Archaeological data often come in the form of counts. Understanding why counts of artifacts, subsistence remains, or features vary across time and space is central to archaeological inquiry. A central statistical method to model such variation is through regression, yet despite sophisticated advances in computational approaches to archaeology, practitioners do not have a standard approach for building, validating, or interpreting the results of count regression. Drawing on advances in ecology, we outline a framework for evaluating regressions with archaeological count data that includes suggestions for model fitting, diagnostics, and interpreting results. We hope these suggestions provide a foundation for advancing regression with archaeological count data to further our understanding of the past. 
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