Hopefully this should get through clearly now with data and output - any thoughts of why ar(1) is not agreeing with SAS?


Paul

Data accessible from below:

eg<-read.csv("http://www.personal.rdg.ac.uk/~sns97aal/eg.csv", header=T, na=".")
eg$run<-as.factor(eg$run)

Output below:
SAS output for first model (no autocorrelation):

                                      Covariance Parameter
                                           Estimates

                                     Cov Parm      Estimate

                                     name          0.003483
                                     run(name)      0.01600
                                     Residual       0.0288

                                   Solution for Fixed Effects

                                         Standard
                Effect       Estimate       Error      DF    t Value    Pr > |t|

                Intercept      1.7264     0.03213       4      53.73      <.0001
                a            -0.00137    0.004333    1114      -0.32      0.7515
                b              0.6129      0.2150    1114       2.85      0.0045
                c            -0.08898     0.01455    1114      -6.11      <.0001


R output which agrees

Random effects:
Formula: ~1 | name
        (Intercept)
StdDev:  0.05900847

Formula: ~1 | run %in% name
        (Intercept)  Residual
StdDev:   0.1265071 0.1697051

                Value  Std.Error   DF  t-value p-value
(Intercept)  1.726390 0.03212781 1114 53.73507  0.0000
cct1.1      -0.001371 0.00433359 1114 -0.31636  0.7518
k21.1        0.612844 0.21502840 1114  2.85006  0.0045
pup01.1     -0.088977 0.01455320 1114 -6.11391  0.0000

SAS output for 2nd model (with autocorrelation):

                                     Covariance Parameter
                                            Estimates

                                      Cov Parm     Estimate

                                      name         0.002904
                                      Variance      0.01671
                                      AR(1)          0.2038
                                      Residual      0.02880

                                   Solution for Fixed Effects

                                         Standard
               Effect       Estimate       Error      DF    t Value    Pr > |t|

                Intercept      1.7274     0.03279       4      52.67      <.0001
                a            -0.00134    0.004366    1114      -0.31      0.7583
                b              0.6034      0.2154    1114       2.80      0.0052
                c            -0.09075     0.01566    1114      -5.79      <.0001


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