[S] differences SAS PROCMIXED and lme

[Siem Heisterkamp <S.H.HEISTERKAMP@amc.uva.nl>]

dear all,
I have allarmig differnces between my interpretaion of SAS output and
S-PLUS lme concerning standard errors of the predicted means. The means
themselves were slightly different.
=====
this is the SPLUS output

:\necosad\_data > summary(basiscat.lme,re=F)
Call:
  Fixed: PCS ~ tijd * CAT + PCSBAS
 Random:  ~ 1
Cluster:  ~ NECNUM 
   Data: rmspl3m 

Estimation Method: RML 
Convergence at iteration: 3 
Restricted Loglikelihood: -1171.087 
Restricted AIC: 2360.174 
Restricted BIC: 2395.049

Variance/Covariance Components Estimate(s):
  Structure: compound symmetry
  Standard Deviation(s) of Random Effect(s)
 (Intercept) 
    4.484634

 Cluster Residual Variance: 29.97762

Fixed Effects Estimate(s):
                  Value Approx. Std.Error  z ratio(C) 
(Intercept)  8.5752692        2.68019729   3.1994918
     tijd12 -0.6220664        0.92257753  -0.6742701
     tijd18 -1.4514370        0.93184751  -1.5575906
        CAT -2.0162583        1.28861974  -1.5646651
     PCSBAS  0.8127410        0.06218279  13.0701923
  tijd12CAT  0.1776739        1.44085896   0.1233111
  tijd18CAT -1.1188441        1.46182566  -0.7653745

 Conditional Correlation(s) of Fixed Effects Estimates 
           (Intercept)       tijd12       tijd18          CAT
PCSBAS    tijd12CAT 
   tijd12 -0.165213876

   tijd18 -0.152608131  0.468059448

      CAT -0.070255654  0.331028476  0.329190675

   PCSBAS -0.953022168  0.005974993 -0.005587017 -0.126515797

tijd12CAT  0.110817754 -0.640328452 -0.299667517 -0.532445421
-0.009105626             
tijd18CAT  0.086962704 -0.298301965 -0.637515103 -0.525330893
0.014388136  0.475987198


cluster means  at 42.11 of the covariate PCSBAS 
by using tapply() on predict.lme( ) output

         1        2 
 6 42.79979 40.65197
12 42.31673 40.22127
18 41.62779 37.98649

"se"  by using tapply() etc 
sqrt(var.basis/n.basis)
           1         2 
 6 0.3906523 0.5298230
12 0.4239170 0.5609732
18 0.4212500 0.5854842

numbers: 
 n.basis
[1] 76 68 66 51 49 46



Using SAS PROCMIXED we have exactly the same fit, same se for the
effects but small differences in LSMEANS
(we checked that the means were computed at the same level of PCSBAS)
and LARGE differences in the se's

to be precise: The SAS estimates for the SE are almost 2 times as large.
What do I wrong in S-PLUS?
(or is my interpretation of the LSMEANS SAS-output wrong)

The syntax in SAS was:

proc sort data=a.rmspl3m; by descending cat descending tijd; run;

proc mixed data=a.rmspl3m order=data method=reml;
  class cat necnum tijd;
  title2 "ANOVA - MIXED - CS - Serial meas.";
  model pcs = cat|tijd pcsbas / solution ;
  repeated tijd/ type=cs sub=necnum(cat) r;
  lsmeans cat|tijd / e;
run;

basiscat.lme<-lme(fixed=PCS~tijd*CAT+PCSBAS,cluster=~NECNUM,random=~1,da
ta=rmspl3m,est.method="RML",na.ac

Dr. S.H. Heisterkamp
University of Amsterdam
Department of Clinical Epidemiology and Biostatistics
room J2-220
PO Box 22700 1100 DE Amsterdam
tel: +31-(0)-20-5668520
fax:+31-(0)-20-6912683
s.h.heisterkamp@amc.uva.nl

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