Subadult age estimation is considered
the most accurate parameter estimated in a subadult
biological profile, even though the methods are deficient
and the samples from which they are based are inappropriate.
The current study addresses the problems that
plague subadult age estimation and creates age estimation
models from diaphyseal dimensions of modern children.
The sample included 1,310 males and females
between the ages of birth and 12 years. Eighteen diaphyseal
length and breadth measurements were
obtained from Lodox Statscan radiographic images generated
at two institutions in Cape Town, South Africa,
between 2007 and 2012. Univariate and multivariate
age estimation models were created using multivariate
adaptive regression splines. k-fold cross-validated 95%
prediction intervals (PIs) were created for each model,
and the precision of each model was assessed. The diaphyseal
length models generated the narrowest PIs
(2 months to 6 years) for all univariate models. The
majority of multivariate models had PIs that ranged
from 3 months to 5 and 6 years. Mean bias approximated
0 for each model, but most models lost precision
after 10 years of age. Univariate diaphyseal length models
are recommended for younger children, whereas multivariate
models are recommended for older children
where the inclusion of more variables minimized the
size of the PIs. If diaphyseal lengths are not available,
multivariate breadth models are recommended. The
present study provides applicable age estimation formulae
and explores the advantages and disadvantages of
different subadult age estimation models using diaphyseal
dimensions.