UC Riverside

OBJECTIVES:Studies of osteoarthritis (OA) in human skeletal remains can come with scalar problems. If OA measurement is noted as present or absent in one joint, like the elbow, results may not identify specific articular pathology data and the sample size may be insufficient to address research questions. If calculated on a per data point basis (i.e., each articular surface within a joint), results may prove too data heavy to comprehensively understand arthritic changes, or one individual with multiple positive scores may skew results and violate the data independence required for statistical tests. The objective of this article is to show that the statistical methodology Generalized Estimating Equations (GEE) can solve scalar issues in bioarchaeological studies. MATERIALS AND METHODS:Using GEE, a population-averaged statistical model, 1,195 adults from the core and one colony of the prehistoric Tiwanaku state (AD 500-1,100) were evaluated bilaterally for OA on the seven articular surfaces of the elbow joint. RESULTS:GEE linked the articular surfaces within each individual specimen, permitting the largest possible unbiased dataset, and showed significant differences between core and colony Tiwanaku peoples in the overall elbow joint, while also pinpointing specific articular surfaces with OA. Data groupings by sex and age at death also demonstrated significant variation. A pattern of elbow rotation noted for core Tiwanaku people may indicate a specific pattern of movement. DISCUSSION:GEE is effective and should be encouraged in bioarchaeological studies as a way to address scalar issues and to retain all pathology information.