get_mmm_start_values: Fit pairwise mixed models to get start values for the...

In JanvandenBrand/jmmm: High Dimensional Joint Models

Fit pairwise mixed models to get start values for the multivariate mixed model

Description

Takes the stacked data and the user defined formulas for the fixed and random effects. Leverages the future.apply package to parallelize along pairs. Using a different number of workers than pairs may result in problems during the optimization process.

Usage

get_mmm_start_values(
  stacked_data,
  fixed,
  random,
  pairs,
  model_families,
  user_initial_values = NULL,
  nAGQ = 11,
  iter_EM = 30,
  iter_qN_outer = 10,
  tol1 = 0.001,
  tol2 = 1e-04,
  tol3 = 1e-08,
  ...
)

Arguments

stacked_data	a list with the stacked data returned by the stack_data() function.
fixed	character string with the fixed model part. This is passed to as.formula().
random	character string with the random model part. This is passed to as.formula().
pairs	a character matrix with the pairs returned by the make_pairs() function.
model_families	a list with family names and indicators returned by the test_input_datatypes() function.
...	arguments passed to GLMMadaptive::mixed_model()

Value

a list with starting values to determine the subject level contributions to the derivates.

JanvandenBrand/jmmm documentation built on May 30, 2022, 9:37 a.m.