Dear R-users: I have some problems working with lme function, and i would be glad if anyone could help me. this kind of analysis i was used to do with PROC MIXED from SAS, but i would like to move to R, for many reasons...
So, the problem is: Imagine the I have 3 factors: fact_A, fact_B and fact_C: The latter I would assume that is random, and the rest of them are fixed. Analysing the structure of the random factor, i found that it's necessary to set up an AR1 model. in a nutshell, it's a 3-way model, but one of the factors is random. working in SAS/ proc mixed I the program to analyside this would be: ######################## proc mixed; class fact_A fact_B fact_C; model y = fact_A fact_B; random fact_c /type=AR1; run; ######################## trying to translate this to R, I tryed after reading ?lme and trying to find any older message at r-help list. ######## library(nlme) GD = groupedData(y~1|fact_C, data=DataFrame) # as I see in the help, it's necessary to covert the data.frame in a groupedData object. lme(fixed= y~fact_A + fact_B, data=GD, random=~1|fact_+C, corr=corAR1(form= ~1|fact_C)) #and trying to run lme function. ######## Am i doing something wrong (or stupid)? 'cause I am not getting the same result. Thanks in advance Rodrigo. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.