[R] lme vs. SAS proc mixed. Point estimates and SEs are the same, DFs are different
John Sorkin
jsorkin at grecc.umaryland.edu
Tue Jun 5 05:38:13 CEST 2007
R 2.3
Windows XP
I am trying to understand lme. My aim is to run a random effects regression in which the intercept and jweek are random effects. I am comparing output from SAS PROC MIXED with output from R. The point estimates and the SEs are the same, however the DFs and the p values are different. I am clearly doing something wrong in my R code. I would appreciate any suggestions of how I can change the R code to get the same DFs as are provided by SAS.
SAS code:
proc mixed data=lipids2;
model ldl=jweek/solution;
random int jweek/type=un subject=patient;
where lastvisit ge 4;
run;
SAS output:
Solution for Fixed Effects
Standard
Effect Estimate Error DF t Value Pr > |t|
Intercept 113.48 7.4539 25 15.22 <.0001
jweek -1.7164 0.5153 24 -3.33 0.0028
Type 3 Tests of Fixed Effects
Num Den
Effect DF DF F Value Pr > F
jweek 1 24 11.09 0.0028
R code:
LesNew3 <- groupedData(LDL~jweek | Patient, data=as.data.frame(LesData3), FUN=mean)
fit3 <- lme(LDL~jweek, data=LesNew3[LesNew3[,"lastvisit"]>=4,], random=~1+jweek)
summary(fit3)
R output:
Random effects:
Formula: ~1 + jweek | Patient
Structure: General positive-definite, Log-Cholesky parametrization
Fixed effects: LDL ~ jweek
Value Std.Error DF t-value p-value
(Intercept) 113.47957 7.453921 65 15.224144 0.0000
jweek -1.71643 0.515361 65 -3.330535 0.0014
John Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)
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