bsitar - Bayesian Super Imposition by Translation and Rotation Growth
Curve Analysis
The Super Imposition by Translation and Rotation (SITAR)
model is a shape-invariant nonlinear mixed effect model that
fits a natural cubic spline mean curve to the growth data and
aligns individual-specific growth curves to the underlying mean
curve via a set of random effects (see Cole, 2010
<doi:10.1093/ije/dyq115> for details). The non-Bayesian version
of the SITAR model can be fit by using the already available R
package 'sitar'. While the 'sitar' package allows modelling of
a single outcome only, the 'bsitar' package offers great
flexibility in fitting models of varying complexities,
including joint modelling of multiple outcomes such as height
and weight (multivariate model). Additionally, the 'bsitar'
package allows for the simultaneous analysis of an outcome
separately for subgroups defined by a factor variable such as
gender. This is achieved by fitting separate models for each
subgroup (for example males and females for gender variable).
An advantage of this approach is that posterior draws for each
subgroup are part of a single model object, making it possible
to compare coefficients across subgroups and test hypotheses.
Since the 'bsitar' package is a front-end to the R package
'brms', it offers excellent support for post-processing of
posterior draws via various functions that are directly
available from the 'brms' package. In addition, the 'bsitar'
package includes various customized functions that allow for
the visualization of distance (increase in size with age) and
velocity (change in growth rate as a function of age), as well
as the estimation of growth spurt parameters such as age at
peak growth velocity and peak growth velocity.