A program for estimating age-at-death from palatal sutures
The Palatal Suture Age Estimator (PSAE) from Hens and Godde (2020) analyzes data scored with a revised palatal suture method based on Mann et al. (1991) with Bayesian Multiple Linear Regression (BMLR). The PSAE comes in two forms: 1) easy-to-use webpages that require no coding ability - just type in or upload your suture scores and the ages are automatically calculated, and 2) R.Data files that are pre-programmed for easy implementation. Note: missing data are not currently supported.
With both versions it is important to know that a single individual ran through the PSAE multiple times will yield a very similar, but slightly different age each time it is processed. This is due to the BMLR resampling the posterior predictive distribution (PPD). If you wish to use the same value for two individuals with identical scores, and for the ages to be standardized across practitioners and over time, please use the values from the look-up table in the appendix to Hens and Godde (2020), which were generated from a single sampling of the PPD.
See Hens and Godde (2020) and/or the User Manual for locations and scoring of the palatal sutures.
Runs the peer-reviewed .RData files within an easy-to-use webpage where practitioners can simply upload a file of palatal suture scores for analysis. No downloading of R is required.
Runs the peer-reviewed .RData files within an easy-to-use webpage where practitioners can simply select palatal suture scores corresponding to their observations. No downloading of R is required.
The Mac version of the peer-reviewed PSAE R.Data file will accept data from two sources: 1) .csv file, and 2) manual inputting. After loading the .RData file, you can simply type in run.palsutures() at the command prompt.
The Windows version of the peer-reviewed PSAE R.Data file will accept data from two sources: 1) .csv file, and 2) manual inputting. After loading the .RData file, you can simply type in run.palsutures() at the command prompt.
Contact Dr. Samantha Hens (shens@csus.edu) as corresponding author or Dr. Kanya Godde (kgodde@laverne.edu) for questions about the PSAE