brokenstick
2.7.0Broken Stick Model for Irregular Longitudinal Data
Overview
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.
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- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-05-1213 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- WARNING2026-05-1112 OK · 0 NOTE · 1 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-146 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 71%
- Documented parameters
- 95%
- Return-value docs
- 100%
- References docs
- 16%
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Code & Tests
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8 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 2.7.0Latest
- unarchivedReturned to CRAN2026-03-13
- archivedRemoved from CRAN2026-03-02issues were not corrected despite reminders
- RR 4.5.0 released · 2025-04-11
- 2.6.02025-03-31 · diff ↗
- unarchivedReturned to CRAN2025-03-31
- archivedRemoved from CRAN2025-03-21the 'maintainer' is deleting notifications unread
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 2.5.02023-03-22 · diff ↗
- 2.4.02022-10-30 · diff ↗
- 2.3.02022-09-07 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 2.1.02022-03-30 · diff ↗
- 2.0.02021-11-11 · diff ↗
Show 3 earlier events
- RR 4.1.0 released · 2021-05-18
- 1.1.02020-11-02
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2026-03-13
- Total releases
- 8 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 462 KB / 4 files
- Download size
- 1.1 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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