mlwinfitIGLS-class: An S4 class that stores the outputs of the fitted IGLS model.
In R2MLwiN: Running 'MLwiN' from Within R

mlwinfitIGLS-class

R Documentation

An S4 class that stores the outputs of the fitted IGLS model.

Description

An MLwiN model run via the IGLS estimation method is represented by an "mlwinfitIGLS" object

Slots

Nobs: Computes the number of complete observations.
DataLength: Total number of cases.
Hierarchy: For each higher level of a multilevel model, returns the number of units at that level, together with the minimum, mean and maximum number of lower-level units nested within units of the current level.
D: A vector specifying the type of distribution to be modelled, which can include 'Normal', 'Binomial' 'Poisson', 'Multinomial', 'Multivariate Normal', or 'Mixed'.
Formula: A formula object (or a character string) specifying a multilevel model.
levID: A character string (vector) of the specified level ID(s).
contrasts: A list of contrast matrices, one for each factor in the model.
xlevels: A list of levels for the factors in the model.
FP: Displays the fixed part estimates.
RP: Displays the random part estimates.
FP.cov: Displays a covariance matrix of the fixed part estimates.
RP.cov: Displays a covariance matrix of the random part estimates.
elapsed.time: Calculates the CPU time used for fitting the model.
call: The matched call.
LIKE: The deviance statistic (-2*log(like)).
Converged: Boolean indicating whether the model has converged
Iterations: Number of iterations that the model has run for
Meth: If Meth = 0 estimation method is set to RIGLS. If Meth = 1 estimation method is set to IGLS.
residual: If resi.store is TRUE, then the residual estimates at all levels are returned.
data: The data.frame that was used to fit the model.
nonlinear: A character vector specifying linearisation method used. The first element specifies marginal quasi-likelihood linearization (N = 0) or penalised quasi-likelihood linearization (N = 1); The second element specifies first (M = 1) or second (M = 2) order approximation.
version: The MLwiN version used to fit the model

An instance of the Class

An instance is created by calling function runMLwiN.

Author(s)

Zhang, Z., Charlton, C.M.J., Parker, R.M.A., Leckie, G., and Browne, W.J. (2016) Centre for Multilevel Modelling, University of Bristol.

Examples

## Not run: 
library(R2MLwiN)
# NOTE: if MLwiN not saved in location R2MLwiN defaults to, specify path via:
# options(MLwiN_path = 'path/to/MLwiN vX.XX/')
# If using R2MLwiN via WINE, the path may look like this:
# options(MLwiN_path = '/home/USERNAME/.wine/drive_c/Program Files (x86)/MLwiN vX.XX/')

## Example: tutorial
data(tutorial, package = "R2MLwiN")

(mymodel <- runMLwiN(normexam ~ 1 + standlrt + (1 + standlrt | school) + (1 | student),
                     data = tutorial))

##summary method
summary(mymodel)

##logLik method
logLik(mymodel)

## End(Not run)

R2MLwiN documentation built on March 31, 2023, 9:17 p.m.