A problem with SPSS is that it does not readily calculate the higher level residuals - there is syntax for it however in the SPSS review on the Centre for Multilevel Modelling software reviews by Alistair Leyland

see SPSS review - University of Bristolhttp://www.bristol.ac.uk/cmm/learning/mmsoftware/spss.html

This book is a pretty comprehensive guide to the recently added capabilities but I found no discussion of the residuals

Multilevel Modeling of Categorical Outcomes Using IBM SPSS

By Ronald H Heck, Scott Thomas, Lynn Tabata

In terms of R you may be interested in R2mlwin which allows you to access mlwin through R

R2MLwiN: Running MLwiN from within R

http://www.bristol.ac.uk/cmm/software/r2mlwin/

If you are looking purely to extract the residuals of both linear and generalized linear mixed models fit with lme4, you can use the residuals.merMod() function in the lme4 library. Residual standard errors can also be accessed with sigma() also in the lme4 library but this only supports merMod class objects and not glmerMod.

I also believe that resid() can handle merMod and glmerMod objects. So a command like:

residuals(model)

or

binnedplot(fitted(model),resid(model))

Could be used to examine normality.

THis should be helpful to those using SPSS to fit multilevel models.

Chris Charlton has now completed the conversion of some of our online Lemma training materials into SPSS. Two Modules have been completed.

• Module 3 on using Multiple regression

• Module 5: Introduction to Multilevel Modelling.

Importantly the latter show you how to use SPSS syntax to calculate higher- level residuals.

You can freely use these materials to teach yourself, and/or use them in courses you are teaching.

The course already has material for MLwiN, Stata and R.

http://www.bristol.ac.uk/cmm/news/57.htmlhttp://www.bristol.ac.uk/cmm/news/57.html

http://www.bristol.ac.uk/cmm/learning/online-course/index.html

http://www.bristol.ac.uk/cmm/news/57.htmlhttp://www.bristol.ac.uk/cmm/news/57.html