[R-sig-ME] lme interaction result strange

[Ista Zahn]

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 at 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 at 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 at r-project.org
>> [mailto:r-sig-mixed-models-bounces at 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 at 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 at 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]]
>> >
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>>
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