The broken stick model describes a set of individual curves by a linear mixed model using second-order linear B-splines. The main use of the model is to align irregularly observed data to a user-specified grid of break ages.
The main functions are:
brokenstick() | Fit a broken stick model to irregular data |
plot() | Plot observed and fitted trajectories by group |
predict() | Obtain predictions on new data |
summary() | Extract object summaries |
The following functions are user-oriented helpers:
coef() | Extract estimated parameters |
fitted() | Calculate fitted values |
get_knots() | Obtain the knots from a broken stick model |
get_omega() | Extract variance-covariance of random effects |
get_r2() | Obtain proportion of explained variance |
model.frame() | Extract model frame |
model.matrix() | Extract design matrix |
residuals() | Extract residuals from broken stick model |
The following functions perform calculations:
set_control() | Set controls to steer calculations |
control_kr() | Set controls for the kr method |
Maintainer: Stef van Buuren stef.vanbuuren@tno.nl
The brokenstick package contains functions for fitting a broken stick model to data, for predicting broken stick curves for new data, and for plotting the results.
van Buuren, S. (2023). Broken Stick Model for Irregular Longitudinal Data. Journal of Statistical Software, 106(7), 1--51. doi:10.18637/jss.v106.i07
van Buuren, S. (2018). Flexible Imputation of Missing Data. Second Edition. Chapman & Hall/CRC. Chapter 11. https://stefvanbuuren.name/fimd/sec-rastering.html#sec:brokenstick #' @keywords internal
brokenstick,
EB, predict.brokenstick