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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "brokenstick" in publications use:'
type: software
license: MIT
title: 'brokenstick: Broken Stick Model for Irregular Longitudinal Data'
version: 2.5.0
doi: 10.18637/jss.v106.i07
identifiers:
- type: doi
  value: 10.32614/CRAN.package.brokenstick
abstract: '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 <https://doi.org/10.18637/jss.v106.i07>
  for additional documentation on background, methodology and applications.'
authors:
- family-names: Buuren
  given-names: Stef
  name-particle: van
  email: stef.vanbuuren@tno.nl
preferred-citation:
  type: article
  title: Broken Stick Model for Irregular Longitudinal Data
  authors:
  - family-names: Buuren
    given-names: Stef
    name-particle: van
    email: stef.vanbuuren@tno.nl
  journal: Journal of Statistical Software
  year: '2023'
  volume: '106'
  issue: '7'
  doi: 10.18637/jss.v106.i07
  start: '1'
  end: '51'
repository: https://growthcharts.r-universe.dev
repository-code: https://github.com/growthcharts/brokenstick
commit: 77c9dab8cea8e6acbf31029e8c8d41bf478fba01
url: https://growthcharts.org/brokenstick/
contact:
- family-names: Buuren
  given-names: Stef
  name-particle: van
  email: stef.vanbuuren@tno.nl