An Introduction to Multivariate Multilevel GLMs

1. An Introduction to Multivariate Multilevel GLMs Hello and welcome

2. Introduction • Multilevel multiprocess models provide an extremely flexible approach to the analysis of a wide array of social science data. • Multilevel modelling allows for the analysis of dependent or clustered data where observations are nested within groups e.g. unemployment of individuals in the same travel to work area. • Most software is limited to single equation systems, unfortunately the social world is not this simple. • Multiprocess modelling allows for correlations in unobservables between different responses, e.g. educational attainment and log wages.

3. Introduction • Multilevel multiprocess analyses involve variables measured at more than one level of a hierarchy. • An obvious hierarchy in education consists of english and maths attainment (bivariate response) for students nested in school classes, and classes nested in schools. • Sabre 5.0 can estimate models for up to 3 simultaneous responses for clustered or panel data. Explanatory variables for the responses can include student characteristics, class and teacher characteristics, or school characteristics.

4. Introduction • Sabre 5 uses quadrature to integrate out the random or unobserved effects • Quadrature is flexible as it can be used with any model, what ever the form • Not limited to analytic results, Poisson~gamma (NBD) or Normal~Normal • Can model simultaneous equation systems, with combinations of response types, e.g. binary response, and Poisson • In our comparisons Sabre 5 seems to outperform a range of commercial and other software systems for the same/similar models • Real advantage of Sabre 5 is that we can go parallel for the analysis of large (data/model) systems on the UK GRID

6. Comparison 3 on the Sabre web site

7. Web site http://sabre.lancs.ac.uk/

8. Sabre 5.0 (Multilevel Multivariate GLMs) • Serial and parallel versions, source code available for download from the sabre site • Sabre features • 3 levels for univariate GLMs • 3 dimensional 2-level GLMs • Sabre site still written for the Sabre 5.0 stand alone version, will be augmented with the sabreR stuff RSN • Sabre uses analytical 1st and 2nd derviatives in its Newton Raphson optimization procedures

9. Sabre-Stata • We have a demo version of this (not being released) • Ok for desktop sabre 5.0 jobs, but not easily extended to submit jobs to the Grid • Problems with the grid submission from Stata, Stata can only have 1 data set open at a time

10. sabreR • R is free software, a community of statisticians maintain the code and continuously update  the programme on a voluntary basis. • R is extremely flexible (has become a de-facto standard among statisticians for the development of statistical software). • The approach is strictly object oriented: everything is an object: data, matrices, results, functions etc with "properties" and "methods" and is classified in "classes" .  • R is also highly extensible through the use of packages, which are user-submitted libraries for specific functions or specific areas of study (now includes the sabreR library) • We will be adding libraries to enable grid job submission and monitoring of a grid sabre job from within your desktop R environment (interim solution available now) • R is more flexible that Stata