The broken stick model describes a set of individual curves by a linear mixed model using second-order linear B-splines. The model can be used to
The user specifies a set of break ages at which the straight lines connect. Each individual obtains an estimate at each break age, so the set of estimates of the individual form a smoothed version of the observed trajectory.
The main assumptions of the broken stick model are:
In order to conform to the assumption of multivariate normality, the user may fit the broken stick model on suitably transformed data that yield the standard normal (\(Z\)) scale.
Three unique features of the broken stick model are:
brokenstick package contains functions to fit, predict and plot data. See the reference page for an overview.
Development of the
brokenstick package was kindly supported by the Healthy Birth Growth and Development knowledge integration (HBGDki) program of the Bill & Melinda Gates Foundation.
brokenstick()for model fitting
predict()for trajectory plotting