A software package for fitting multilevel models. An important
feature of MLwiN is its graphical interfaces. These allow the user
easily to set up, fit and manipulate models. There are windows for
data manipulation, plotting, viewing the progress of iterations etc.
Predictions from fitted models can be specified directly using
standard statistical notation with direct links to various kinds of
derived graphs, which are automatically updated as model parameters
change. Likewise, posterior residual estimates and functions of them
can be linked directly to graphs, for example for model diagnostics.
Multivariate models are simple to specify using a special input
screen. Complex variance functions can be specified and the software
will allow linear and non-linear modelling of variances as functions
of explanatory variables with an interactive screen, which displays
the resulting model in standard notation.
Markov Chain Monte Carlo (MCMC) Bayesian modelling is incorporated
with detailed visual diagnostics. Parametric nd non-parametric
bootstrapping is available and an iterated bootstrap has been
implemented for unbiased estimation with multilevel generalised
A few of its features
Names window (where you can see all the variables)
Equations window (showing what model has been fitted and the
Variance function window (to calculate the residual variance at any
Predictions window (to calculate predicted values for each
individual in the dataset, specifying what should be included in the
Graphs (here the user has selected the country line that seems to be
different from the others and asked that points relating to this
country be drawn in red in all graphs, to help in deciding whether
this is an outlier; the country is the Netherlands, as the user
would have seen when they clicked on the line).