[R] lme vs. SAS proc mixed. Point estimates and SEs are the same, DFs are different

[John Sorkin]

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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