Displaying 2 results from an estimated 2 matches for "solutionr".
Did you mean:
solution
2012 Nov 07
2
LMER vs PROC MIXED estimates
...d that the estimates are coming different.
My SAS code is as follows (trying to randomise X2 and Intercept):
PROC MIXED DATA = <DATASET NAME> NAMELEN=100 METHOD=REML MAXITER=1000;
CLASS GEOGRAPHY;
MODEL y = X1 X2 X3/SOLUTION;
RANDOM INTERCEPT X2/SOLUTION SUBJECT = GEOGRAPHY;
ODS OUTPUT SOLUTIONR=RANDOM_EFFECT;
ODS OUTPUT SOLUTIONF= FIXED_EFFECT;
RUN;
the equivalent code that I was writting in R is as follows:
testdata <- read.csv("adstest.csv",header=TRUE,sep=",")
attach(testdata)
library(lme4)
options(contrasts = c(factor = "contr.SAS",ordered = &q...
2008 May 22
1
mixed model resuts from SAS and R
...ficients are 0 vs. in R the beta-s are non zero.
The variables of the data are nidl, time, and sub (for subject). Time and
nidl are continuous variables. I am applying random coefficients model.
Any input is greatly appreciated, Thanks, Aldi
1. mixed model in SAS:
======================
ods output SolutionR = out1.randomnidltest2;
proc mixed data = a1 ;
class sub ;
model nidl = time / solution ;
random int time / sub = sub solution;
run;
ods output close;
2. mixed model in R:
====================
a1<-read.table(file="c:\\aldi\\a1.txt",sep=",",header=T)
library(nlme)
fm...