make_basis

This function creates the basis function of a second-order (linear) splines
at a user-specific set of break points.

Data on multiple individuals through time are often sampled at
times that differ between persons. Irregular observation times can severely
complicate the statistical analysis of the data. The broken stick model
approximates each subject’s trajectory by one or more connected line segments.
The times at which segments connect (breakpoints) are identical for all
subjects and under control of the user. A well-fitting broken stick model
effectively transforms individual measurements made at irregular times into
regular trajectories with common observation times. Specification of the
model requires three variables: time, measurement and subject. The
model is a special case of the linear mixed model, with time as a linear
B-spline and subject as the grouping factor. The main assumptions are:
subjects are exchangeable, trajectories between consecutive breakpoints are
straight, random effects follow a multivariate normal distribution, and
unobserved data are missing at random. The package contains functions for
fitting the broken stick model to data, for predicting curves in new data
and for plotting broken stick estimates. The package supports two
optimization methods, and includes options to structure the
variance-covariance matrix of the random effects. The analyst may use the
software to smooth growth curves by a series of connected straight lines, to
align irregularly observed curves to a common time grid, to create synthetic
curves at a user-specified set of breakpoints, to estimate the time-to-time
correlation matrix and to predict future observations. See
<doi:10.18637/jss.v106.i07> for additional documentation on background,
methodology and applications.

Stef van Buuren

brokenstick

Broken Stick Model for Irregular Longitudinal Data

make_basis function

<dl><dt>x</dt>
<dd>numeric vector</dd>
<dt>xname</dt>
<dd>predictor name. Default is <code>"x"</code></dd>
<dt>internal</dt>
<dd>a vector of internal knots, excluding boundary knots</dd>
<dt>boundary</dt>
<dd>vector of external knots</dd>
<dt>degree</dt>
<dd>the degree of the spline. The broken stick model
requires linear splines, so the default is <code>degree = 1</code>.
Setting <code>degree = 0</code> yields (crisp) dummy coding, and one
column less than for <code>degree = 1</code>.</dd>
<dt>warn</dt>
<dd>a logical indicating whether warnings from <code><a href="/link/splines%3A%3Abs()?package=brokenstick&version=2.6.0" data-mini-rdoc="brokenstick::splines::bs()">splines::bs()</a></code>
should be given.</dd></dl>

Arguments

Author

Create linear splines basis — make_basis

<dl>

<dt>x</dt>
<dd>numeric vector</dd>


<dt>xname</dt>
<dd>predictor name. Default is <code>"x"</code></dd>


<dt>internal</dt>
<dd>a vector of internal knots, excluding boundary knots</dd>


<dt>boundary</dt>
<dd>vector of external knots</dd>


<dt>degree</dt>
<dd>the degree of the spline. The broken stick model
requires linear splines, so the default is <code>degree = 1</code>.
Setting <code>degree = 0</code> yields (crisp) dummy coding, and one
column less than for <code>degree = 1</code>.</dd>


<dt>warn</dt>
<dd>a logical indicating whether warnings from <code><a href='https://rdrr.io/r/splines/bs.html'>splines::bs()</a></code>
should be given.</dd>

</dl>

make_basis: Create linear splines basis

Description

Usage

Value

Arguments

Author