[R] simple main effect.

Ista Zahn istazahn at gmail.com
Sun Dec 20 18:45:57 CET 2009


Well, the F value is just MS_effect/MS_error. So you run the original
model, run the subset models, but disregard the F values. To calculate
the correct F values, divide MS_effect from the subset model by the
MS_error term from the original (full) model. It's not really a matter
of learning how to do it in R -- you're just doing simple division.

-Ista

On Sun, Dec 20, 2009 at 12:28 PM, Or Duek <orduek at gmail.com> wrote:
> Thank you very much Ista.
> Can you please be a bit more specific as to using the overall error. I don't
> know how to actually do it in R.
> thank you,
> Or.
>
> On Sun, Dec 20, 2009 at 7:09 PM, Ista Zahn <istazahn at gmail.com> wrote:
>>
>> Hi Or,
>> I understand your question (and am not sure what the confusion is
>> about actually). Just like you said, you want to know the effect of A
>> at B=1, and the effect of A at B=2. In this case, you want to know if
>> drug has a significant effect for those with strain one, and whether
>> drug has a significant effect for those with strain two. So the good
>> part is, I understand the question.
>>
>>
>> The bad part is that unfortunately I don't know how to do it with
>> aov(). Also, I'm not a stats guru and could easily be wrong about the
>> following advice. You've been warned!
>>
>> If you didn't have a mixed model, I would tell you to run the model
>> using lm() twice, setting drug = 1 as the reference group the first
>> time, and drug = 2 as the reference group the second time, but this
>> won't work in your case. The best I can offer is a suggestion to run
>> the model separately for each level of drug. Note that you can and
>> should use the error term from the overall model though -- you will
>> have to do this "by hand" (just divide  MS_effect from the subset
>> model by MS_error from the full model, and evaluate using df_error
>> from the overall model). So basically, I'm suggesting that you do
>>
>> Data.drug1 <- subset(Data, drug == "1")
>> aov.model.drug.1 <- aov(dependent~(exposure*strain) +
>> Error(subject/exposure) + (strain), data=Data.drug1)
>> summary(aov.model.drug.1)
>>
>> Data.drug2 <- subset(Data, drug == "2")
>> aov.model.drug.2 <- aov(dependent~(exposure*strain) +
>> Error(subject/exposure) + (strain), data=Data.drug2)
>> summary(aov.model.drug.2)
>>
>> Good luck!
>>
>> -Ista
>>
>> On Sun, Dec 20, 2009 at 11:35 AM, Or Duek <orduek at gmail.com> wrote:
>> > For some reasion I wasn't able to use TukeyHSD - I think because I need
>> > to
>> > set the different levels under a second variable.
>> > Tukey only helps me when I have more than 2 levels of same variable.
>> > Thanl you.
>> > On Sun, Dec 20, 2009 at 6:32 PM, S Devriese <sdmaillist at gmail.com>
>> > wrote:
>> >
>> >> On 12/20/2009 04:56 PM, Or Duek wrote:
>> >> > I don't have missing data.
>> >> > about what I need.
>> >> > Lets say the drug*strain interaction is significant - now I want to
>> >> > check
>> >> > for drug under the levels of strain - compare drug 1 and 2 only on
>> >> > strain
>> >> 1
>> >> > and then only on strain 2.
>> >> > Or I'd like to compare the strains under levels of exposure.
>> >> > This is the kind of data I fail to see in summary() but it is
>> >> > important
>> >> to
>> >> > understand the interactions.
>> >> > thank you.
>> >> >
>> >>
>> >> Do you main pairwise multiple comparison tests like Tukey Honest
>> >> Significant Difference tests? Then you could use TukeyHSD in the stats
>> >> package or see the DTK package (Dunnett-Tukey-Kramer Pairwise Multiple
>> >> Comparison Test Adjusted for Unequal Variances and Unequal Sample
>> >> Sizes)
>> >>
>> >> Stephan
>> >>
>> >
>> >        [[alternative HTML version deleted]]
>> >
>> > ______________________________________________
>> > R-help at r-project.org mailing list
>> > https://stat.ethz.ch/mailman/listinfo/r-help
>> > PLEASE do read the posting guide
>> > http://www.R-project.org/posting-guide.html
>> > and provide commented, minimal, self-contained, reproducible code.
>> >
>>
>>
>>
>> --
>> Ista Zahn
>> Graduate student
>> University of Rochester
>> Department of Clinical and Social Psychology
>> http://yourpsyche.org
>
>



-- 
Ista Zahn
Graduate student
University of Rochester
Department of Clinical and Social Psychology
http://yourpsyche.org




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