MIXED MODELS FOR REPEATED (LONGITUDINAL) DATA

I need to add a section on references. Some good ones on the web are:http://www.uoregon.edu/~robinh/mixed_sas.htmlhttp://www.ats.ucla.edu/stat/sas/faq/anovmix1.htmhttp://www.ats.ucla.edu/STAT/SAS/library/mixedglm.pdfhttp://ssc.utexas.edu/consulting/answers/sas/sas94.htmlhttp://quiro.uab.es/jpa/pdf/Littell_mixed_JAS.pdfGood coverage of alternative covariance structureshttp://cda.morris.umn.edu/~anderson/math4601/gopher/SAS/longdata/structures.pdfThe main reference for SAS Proc Mixed isLittle, R.C., Milliken, G.A., Stroup, W.W., Wolfinger, R.D., & Schabenberger, O. (2006)SAS for mixed models, Cary, NC SAS Institute Inc.The Overall et al. reference that I referred to isOverall, J. E., Ahn, C., Shivakumar, C., & Kalburgi, Y. (1999). Problematic formulationsof SAS Proc.Mixed models for repeated measurements. Journal of BiopharmaceuticalStatistics, 9, 189-216. (That probably is not a journal that you read on a monthly basis,but the article is not too technical.)The classic reference for R is Penheiro, J. C. & Bates, D. M. (2000) Mixed-effects modelsin S and S-Plus. New York: Springer.For imputation the best reference isShafer, J. L. & Olson, M. K. (1998). Multiple imputation for multivariate missing-dataproblems: A data analysts perspective. Multivariate Behavioral Research, 33, 545-571