Data from: A hierarchical Bayesian approach for handling missing classification data

Alison C. Ketz, Therese L. Johnson, Mevin B. Hooten & M. Thompson Hobbs
Ecologists use classifications of individuals in categories to understand composition of populations and communities. These categories might be defined by demographics, functional traits, or species. Assignment of categories is often imperfect, but frequently treated as observations without error. When individuals are observed but not classified, these “partial” observations must be modified to include the missing data mechanism to avoid spurious inference. We developed two hierarchical Bayesian models to overcome the assumption of perfect assignment to...
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These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
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