1. An Alternative Package for Estimating Multivariate Generalised Linear Mixed Models in R Damon Berridge, Robert Crouchley & Daniel Grose, Lancaster University, U.K.

2. Outline A motivating example Multivariate models: some comparisons Enabling technology Demo Conclusions

3. A motivating example (BHPS) Sample of males who were employed and earning a wage at some point over the period 1991-2003. Gives a total of 5285 individuals with a sequence of responses that occurred somewhere in the 1991- 2004 interval. At the 1st sample point of the survey (1991) there were was 2316 individuals of whom 945 of these males had some form of training in the previous 12 months. 106 had been promoted in the previous 12 months.

4. What is the effect of training & promotion on wages? Suppose we want to disentangle the dependencies between: Promotion (P=1,0) in the last 12 months (latent variable P*) Training (T=1,0) in the last 12 months (latent variable T*) Current wages (W)

5. A correlated random effects model

6. Multivariate models: some comparisons ModelgllammSASSabre1Sabre48 T & P125 days12 years1h42'3'31 W & T & P20 years500 years115h45'2h45' ModelObsCasesVarsSizeMethod T & P62,0445,28514334.2 MBAQ (16x16) W & T & P93,0665,28521751.3 MBAQ (12x16x16)

7. Enabling technology for GRID computing All you need is: 1.An internet connection 2.The installation of our multiR or sabreR packages for R 3.A certificate to identify the client to the host - typically a GRID certificate

8. Points to note Users do not need to install or be familiar with grid-proxy tools or any other GRID-related software. When statistical modelling, there is very little difference between using the Sabre library from within R on the desktop, and using the Sabre library from within R on the GRID.

9. Demo sabrer_grid_vs_local_demo.mov

10. Conclusions This approach makes all the GRID middleware invisible and thus removes the biggest barrier to take up. This approach can provide researchers with more sophisticated statistical modelling tools and help increase their understanding of complex processes and thus help them to undertake more effective research. Researchers do not need to let their large-scale computational statistics problems be limited by the developments of the big statistics software houses like SAS and Stata.

11. For further information on sabreR, see the Sabre web site: http://sabre.lancs.ac.uk/ Sabre web page

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