brokenstick-class: Class 'brokenstick'
In stefvanbuuren/brokenstick: Broken Stick Model for Irregular Longitudinal Data

brokenstick-class

R Documentation

Class `brokenstick`

Description

The main fitting function brokenstick() returns an object of class brokenstick. This object collects the fitted broken stick model.

Details

The package exports S3 methods for the brokenstick class for the following generic functions: coef(), fitted(), model.frame(), model.matrix(), plot(), predict(), print(), residuals() and summary().

The package exports the following helper functions for brokenstick objects: get_knots(), get_omega() and get_r2().

A brokenstick object is a list with the following named elements:

Elements

call: Call that created the object
names: A named list with three elements ("x", "y", "g") providing the variable name for time, outcome and subject, respectively.
internal: Numeric vector of with internal knots.
boundary: Numeric vector of length 2 with the boundary knots.
degree: The degree of the B-spline. See splines::bs(). Support only the values of 0 (step model) or 1 (broken stick model).
method: String, either "kr" or "lmer", identifying the fitting model.
control: List of control options returned by set_control() used to set algorithmic details.
beta: Numeric vector with fixed effect estimates.
omega: Numeric matrix with variance-covariance estimates of the broken stick estimates.
sigma2: Numeric scalar with the mean residual variance.
sample: A numeric vector with descriptives of the training data.
light: Should the returned object be lighter? If light = TRUE the returned object will contain only the model settings and parameter estimates and not store the sigma2j, sample, data, imp and mod elements. The light object can be used to predict broken stick estimates for new data, but does not disclose the training data and is small.
hide: Should the output for boundary knots be hidden? Can be "right", "left", "boundary", "internal" or "none". The default is "right".
sigma2j: Numeric vector with estimates of the residual variance per group. Only used by method "kr".
data: The training data used to fit the model.
imp: The imputations generated for the missing outcome data. Only for method = "kr".
mod: For method = "kr": A named list with four components, each of class coda::mcmc. For method = "lmer": An object of class lme4::merMod.