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) Pe ́cina cave excava- tions in Croatia and stone finds from the Bronze Age site of Akrotiri, Thera, Greece. This is followed by a dis- cussion 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.
Bibliographical noteFunding Information:
The application of multilevel modelling to archaeological data was part of the PhD research by C.L.F funded by AHRC-SWW DTP , UK and British Association of Biological Anthropology and Osteoarchaeology, UK . The relationship between spatial statistics and archaeological theory, and the excavations in Mala Pećina were part of the PhD research by K.P.T supported by Matti Egon II scholarship of the Greek Archaeological Committee , UK and the British Cave Research Association , UK. Research on the Akrotiri spheres has been partially supported by the KA201-079065 EU grant. Authors would like to thank, Dr Ivan Drnić for providing access to the Mala Pećina data, Dr Tania Devetzi and Professor Christos Doumas who made the material from Akrotiri spheres available, and Argyris Mavromatis, Lefteris Zorzos and Maria Karra for their help on Santorini.
© 2021 The Authors
- archaeological data
- multilevel modelling
- Bayesian statistics in archaeology
- Akrotiri Thera
- Neolithic Adriatic