MLwiN

Author: The Centre for Multilevel Modelling (CMM), Univers
Contact: http://www.cmm.bristol.ac.uk/MLwiN/
Description: Multilevel modelling has rapidly become established as the appropriate tool for modelling data with complex hierarchical structures. 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. 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 linear models.
Analyses: Dimensionality; Factor/Latent Structure; Multidimensional Models; Simulation/Resampling
System Requirements: Windows
Measurement Model: Statistical
License Type: Commercial
Documentation: free training version; free for UK academics; 30-d