An Introduction to Multivariate Multilevel GLMs Hello and welcome

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.

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.

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

Comparison 3 on the Sabre web site

Web site

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 1 st and 2 nd derviatives in its Newton Raphson optimization procedures

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

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)libraries –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