NEWS.md

brokenstick 2.5.0

brokenstick 2.4.0

Major changes:

Minor changes:

brokenstick 2.3.0

brokenstick 2.2.0

Major changes:

  1. Changes the default number of knots in brokenstick() to 5. The former default produced a solution without internal knots. The new default produces a generally more informative starting model when the user does not specify knots (using knots = c(..., ...)) or the number of knots (using k = ...).
  2. Replaces the strip_data argument in predict() by the a more intuitive include_data argument. By default, observed data are now included into the predictions, similar to predict.lm().
  3. Turns error Argument 'newdata' is required for a light brokenstick object. of brokenstick() into a warning and returns NULL.
  4. Updates the vignette Broken Stick Model for Irregular Longitudinal Data to sync with revision for JSS.

Minor changes:

brokenstick 2.1.0

Incorporate changes and updates required by JSS

brokenstick 2.0.2

brokenstick 2.0.1

brokenstick 2.0.0

Main changes

  1. Function brokenstick() in version 2.0.0 sets the Kasim-Raudenbush sampler as the default method. The former method lme4::lmer() remains available by setting method = "lmer" argument.

  2. Version 2.0.0 adopts the variable names of the coda package (e.g., start, end, thin, niter, and so on) and stores the results of the Kasim-Raudenbush sampler as objects of class mcmc.

  3. For method = "kr" one may now inspect the solution of the sampler by standard functions from the coda package. For method = "lmer" we can apply functions from the lme4 package for merMod objects.

  4. Version 2.0.0 redefines the brokenstick class. New entries include call, formula, internal, sample, light, data, imp and mod. Removed entries are knots (renamed to internal) and draws (renamed to imp). We may omit the newdata argument for the training data. Setting light = TRUE creates a small version of the brokenstick object. Objects of class brokenstick are not backwards compatible, so one should regenerate objects of class brokenstick in order use newer features in 2.0.0.

  5. Version 2.0.0 conforms to classic model fitting interface in R. Renames the new_data argument to newdata to conform to predict.lm(). Methods plot() and predict() no longer require a newdata argument. All special cases of predict() updated and explained in documentation and examples.

  6. Version 2.0.0 adds methods coef(), fitted(), model.frame(), model.matrix(), print() and summary for the brokenstick object.

  7. Simplifies algorithmic control. Renames control_brokenstick() to set_control() and removes a layer in the control list.

Minor changes

brokenstick 1.1.1

brokenstick 1.1.0

This version adds a couple of minor alterations.

brokenstick 1.0.0

brokenstick 0.78.0

brokenstick 0.77.0

brokenstick 0.76.0

brokenstick 0.75.0

brokenstick 0.72.1

brokenstick 0.72.0

brokenstick 0.71.0

brokenstick 0.70.1

brokenstick 0.70.0

brokenstick 0.62.0

brokenstick 0.61.0

brokenstick 0.60.0

brokenstick 0.55

brokenstick 0.54

brokenstick 0.53

Here 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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brokenstick documentation built on March 31, 2023, 9:24 p.m.