Detecting variability: A study on the application of bayesian multilevel modelling to archaeological data. Evidence from the Neolithic Adriatic and the Bronze Age Aegean

The detection and interpretation of variability in archaeological data has been a long-standing effort in the field. This paper aims to introduce the application of Bayesian multilevel modelling as a tool for the detection of variability at levels within nested archaeological data. Model structure, ways of construction, and the potential of using variability information to enhance archaeological interpretations is presented. This is demonstrated through the analysis of two case study datasets: Neolithic pottery finds from Mala (Nova) Pec?ina cave excavations in Croatia and stone finds from the Bronze Age site of Akrotiri, Thera, Greece. This is followed by a discussion of the multilevel model results and the possible interpretations that can be derived from them. Finally, propositions are made on how these and other models can be extended.