Dear R users,

I have been working on replicating some linear mixed models from SAS.  The
first one matches perfectly when the SAS model is simple with the three
separate factors.

fit=lme(var~group+Event_name+Died,
    data=liv34,
    random=~1|ID)
anova.lme(fit, type="marginal", adjustSigma=F)

However, once I put an interaction into the formula the values don't match.

fit=lme(var~group+Event_name+Died+Event_name*Died,
    data=liv34,
    random=~1|ID)
anova.lme(fit, type="marginal", adjustSigma=F)

                          numDF denDF     F-value      p-value
(Intercept)               1        91       111.20483  <.0001
group                      1        23        0.46632     0.5015
Event_name            5        91        1.14042     *0.3449*
Died                       1        23        0.50989    * 0.4824*
Event_name:Died     5       91        1.10436     0.3637
Done.

The numbers *bold* don't match up.  They should be approximately .0290 and
.1318 respectively.  The other two are still exact matches.  I know looking
for exact matches is ambitious but the numbers should be at least similar
that the conclusions don't change so drastically.

Any thoughts as to why this discrepancy is happening would be most
appreciated.

Regards,

Charles

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