fitted.GLMMMCMC: Fitted profiles in the GLMM model

In mixAK: Multivariate Normal Mixture Models and Mixtures of Generalized Linear Mixed Models Including Model Based Clustering

Fitted profiles in the GLMM model

Description

It calculates fitted profiles in the (multivariate) GLMM with a normal mixture in the random effects distribution based on selected posterior summary statistic of the model parameters.

Usage

## S3 method for class 'GLMM_MCMC'
fitted(object, x, z,
  statistic=c("median", "mean", "Q1", "Q3", "2.5%", "97.5%"),
  overall=FALSE, glmer=TRUE, nAGQ=100, ...)

Arguments

object	object of class GLMM_MCMC.
x	matrix or list of matrices (in the case of multiple responses) for “fixed effects” part of the model used in the calculation of fitted values.
z	matrix or list of matrices (in the case of multiple responses) for “random effects” part of the model used in the calculation of fitted values.
statistic	character which specifies the posterior summary statistic to be used to calculate fitted profiles. Default is the posterior median. It applies only to the overall fit.
overall	logical. If TRUE, fitted profiles based on posterior mean/median/Q1/Q3/2.5%/97.5% of the model parameters are computed. If FALSE, fitted profiles based on posterior means given mixture component are calculated. Note that this depends on used re-labelling of the mixture components and hence might be misleading if re-labelling is not succesfull!
glmer	a logical value. If TRUE, the real marginal means are calculated using Gaussian quadrature.
nAGQ	number of quadrature points used when glmer is TRUE.
...	possibly extra arguments. Nothing useful at this moment.

Value

A list (one component for each of multivariate responses from the model) with fitted values calculated using the x and z matrices. If overall is FALSE, these are then matrices with one column for each mixture component.

Author(s)

Arnošt Komárek [e-mail]

See Also

GLMM_MCMC.

Examples

### WILL BE ADDED.

mixAK documentation built on Sept. 25, 2023, 5:08 p.m.