I have checked the contrasts and 'unfortunately' they are identical.  Is
that a statistically correct avenue to just take the interaction term from
the interaction model and use the first ones?  That seems odd to me as the
numbers aren't the same even in the SAS output between the models.  I
certainly appreciate your prior suggestion but perhaps you or someone else
has another idea?  Something else seems to be strange, perhaps the syntax
needs to be different when doing an interaction term?

Thanks,
Charles

On Tue, May 1, 2012 at 2:02 PM, Ista Zahn <istazahn@gmail.com> wrote:

> Hi Charles,
>
> Ask yourself what the Event_name and Died terms represent in this
> model. When you understand that, you'll understand why you need to
> know what contrasts were used if you hope to correctly interpret these
> terms.
>
> Alternatively, you can interpret the Event_name and Died terms from
> the first model (without the interaction term), and interpret just the
> interaction term from this model (so-called type II sums of squares by
> some).
>
> Best,
> Ista
>
> On Tue, May 1, 2012 at 2:54 PM, Charles Determan Jr <deter088@umn.edu>
> wrote:
> > I have yet to attempt the contrast suggestion yet but here is the SAS
> output
> > to complement the R.
> >
> > SAS output for the simple and interaction models.  I have presented the
> Type
> > III tests for simplicity.  As you can see from my prior R output, the DFs
> > match exactly.  The only variation is with the F and p value of the
> > Event_name and Died in the interaction model.
> >
> > Type 3 Tests of Fixed Effects
> >
> > Effect            NumDF DenDF F Value Pr > F
> >
> > group                1            23          0.65    0.4293
> >
> > Event_name     5            96          2.09    0.0738
> >
> > Died                  1            23          1.83    0.1889
> >
> >
> >
> > Type 3 Tests of Fixed Effects
> >
> > Effect                    NumDF DenDF     F Value Pr > F
> >
> > group                       1              23           0.47     0.5015
> >
> > Event_name            5              91           2.62    0.0290
> >
> > Died                         1              23           2.44     0.1318
> >
> > Event_name*Died 5              91          1.10     0.3637
> >
> >
> > R output of interaction model
> >
> >                          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.
> >
> >
> > Regards,
> >
> > Charles
> >
> >
> >
> > On Tue, May 1, 2012 at 1:39 PM, Thompson,Paul
> > <Paul.Thompson@sanfordhealth.org> wrote:
> >>
> >> There is another issue. From the error df, it seems like this is a
> >> multi-level/RM/multiple obs study, and SAS and R do not always agree on
> the
> >> computation of the df, as well as the type of SS that is being
> computed. You
> >> need to present both outputs, so that we can see both.
> >>
> >> I know almost nothing about R, and so my comments may not be relevant.
> >>
> >> -----Original Message-----
> >> From: r-sig-mixed-models-bounces@r-project.org
> >> [mailto:r-sig-mixed-models-bounces@r-project.org] On Behalf Of Ista
> Zahn
> >> Sent: Tuesday, May 01, 2012 12:51 PM
> >> To: Charles Determan Jr
> >> Cc: r-sig-mixed-models@r-project.org
> >> Subject: Re: [R-sig-ME] lme interaction result strange
> >>
> >> Hi Charles,
> >>
> >> My first guess is that you have (a) categorical variable(s) in your
> >> predictors, and that the contrasts in SAS are different than those in
> >> R.
> >>
> >> Best,
> >> Ista
> >>
> >> On Tue, May 1, 2012 at 1:39 PM, Charles Determan Jr <deter088@umn.edu>
> >> wrote:
> >> > 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
> >> >
> >> >        [[alternative HTML version deleted]]
> >> >
> >> > _______________________________________________
> >> > R-sig-mixed-models@r-project.org mailing list
> >> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >>
> >> _______________________________________________
> >> R-sig-mixed-models@r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >>
> >> -----------------------------------------------------------------------
> >> Confidentiality Notice: This e-mail message, including any attachments,
> >> is for the sole use of the intended recipient(s) and may contain
> >> privileged and confidential information.  Any unauthorized review, use,
> >> disclosure or distribution is prohibited.  If you are not the intended
> >> recipient, please contact the sender by reply e-mail and destroy
> >> all copies of the original message.
> >>
> >
>

	[[alternative HTML version deleted]]

