mixoutsamp

Object of class <code>lme</code> containing the fitted LME model

model

Data frame containing data for which to make predictions.
The response variable should be set to NA for the rows of the data the user wishes to make predictions for.
The columns in the data should have the same names as those used to fit the model.
The variables should also be of the same type as in the data used to fit the mixed model (numeric, factor etc).

newdata

This function allows the user to make out-of-sample predictions from an LME model.

The landmark approach allows survival predictions to be
updated dynamically as new measurements from an individual are recorded.
The idea is to set predefined time points, known as "landmark times",
and form a model at each landmark time using only the individuals in the
risk set. This package allows the longitudinal data to be modelled
either using the last observation carried forward or linear mixed
effects modelling. There is also the option to model competing risks,
either through cause-specific Cox regression or Fine-Gray regression.
To find out more about the methods in this package, please see
<https://isobelbarrott.github.io/Landmarking/articles/Landmarking>.

Isobel Barrott

Landmarking

mixoutsamp: Calculate point estimates from a linear mixed effects (LME) model for new data

Description

Usage

Arguments

Value