This version adds a couple of minor alterations.
description
field\dontrun{}
directivesparse_formula()
to remove :::
from examples:
and _
charactersoldfriends.Rmd
predict.brokenstick()
examplehttps://github.com/growthcharts/brokenstick/
plot.brokenstick()
with the ability to plot imputed trajectoriesweightloss
datadegree > 1
what
to plot.brokenstick()
predict()
when the group variable is a factorboundary
parametermodel.matrix()
removes rows with NA
if degree = 0
hardhat
and recipes
brokenstick
object smaller since no blueprints are storedrecipe
interface to the brokenstick()
functionggplot2
to suggests
install.on.demand()
function from mice
recipes::recipe()
to inform R package installation process growthstandards
plot
examples ggplot2
out-of-range/missing messages through better filteringdegree = 0
This version jump illustrates big and breaking changes:
brokenstick
adopted the tidymodels
philosophy, and now includes
a dependency on hardhat
. It is now possible to fit a model using
five different interfaces. There is no need anymore the hardcode variable
names in the source data.
This version introduces a new estimation method, the Kasim-Raudenbush
sampler. The new method is more flexible and faster than lme4::lmer()
when the number of knots is large.
This version introduces two simple correlation models that may be used to smooth out the variance-covariance matrix of the random effects.
The definition of the brokenstick
class has changed. Objects of
class brokenstick
do no longer store the training data.
The brokenstick_export
class is retired.
The predict()
function is fully rewritten as has now a new interface.
Since the brokenstick
class does not store the training data anymore,
the predict()
function now obtains a new_data
argument. Syntax that
worked for brokenstick
package before 0.70.0
does not work anymore
and should be updated. The shape
argument replaces the output
argument.
The plot()
function is rewritten, and now requires a new_data
specification.
Retired functions: brokenstick()
replaces fit_brokenstick()
,
predict.brokenstick()
replaces predict.brokenstick_export()
,
get_r2()
replaces get_pev()
Removed functions: get_data()
, get_X()
, export()
ggplot
objects sharper in vignettes by svglite
pkg
argument in plot.brokenstick()
rbokeh
hbgd
(which is no longer developed) by growthstandards
packagesmocc_50
/fit_50
by smocc_200
/fit_200
NEWS.md
file to track changes to the packagesmocc_50
and fit_50
demo datasmocc.hgtwgt
, smocc_hgtwgt
and fit_206 datasets
get_pev()
for proportion explained varianceget_knots()
gets a what
argumentplot()
plot()
ggplot2
ggplot2
plot defaultshow_references
flag to FALSEHere is the abstract of the lecture:
Broken stick model for individual growth curves
Stef van Buuren
1) Netherlands Organization for Applied Scientific Research TNO 2) Utrecht University
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
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 that the development between the break ages follows a straight line, and that the broken stick estimates follow a common multivariate normal distribution. 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-score) scale.
This lecture outlines the model and introduces the brokenstick R package.
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