Burnham and Anderson (2002) provide the formulas for computing AIC from any model that generates either a log-liklihood value (Page 61) or a residual error (Page 63) so you can generate an AIC for pretty much any statistical model. SAS provides AIC as standard output on some procedures such as Proc Mixed and as parts of output data sets on some others such as Proc Reg. Many procedures do not provide an option for outputting AIC such as GLM.
Jim ><(((º> ><(((º> ><(((º> ><(((º> ><(((º> ><(((º> Jim Novak Biological Sciences Department 1162 life Sciences Annex Eastern Illinois University Charleston, IL 61920 (217) 581-6385 (217) 581-7141 (FAX) [email protected] http://www.ux1.eiu.edu/~jmnovak/ ><(((º> ><(((º> <º)))>< ><(((º> ><(((º> ><(((º> Confidentiality Notice: This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. On Oct 26, 2011, at 10:32 AM, Minda Berbeco wrote: > Hello, > > I am looking for recommendations for programs to use for calculating AIC > scores. I've looked into the AICcmodavg package with R, but the associated > instructional material is not clear and I have not been able to get it to > work. I hear that SAS is good as well, but have not found a good book that > tells me how to create AIC scores (recommendations would be appreciated). > I've also looked into SPSS, which according to IBM can create AIC scores, > but have had no success. > > Any recommendations for programs and clear associated instructional material > with information on how to run the program, write the code etc. would be > greatly appreciated. > > Thanks, > > Minda Berbeco > Viticulture and Enology, UC Davis > [email protected]
