Repeated measures Tukey

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Repeated measures Tukey

Francesc Pla Juncà
Thanks in advance for your help.

I am running a repeated measures ANOVA in r. The same group undergoes to
four different treatment conditions. So, all individuals are treated with
treatments A, B, C and D in four different occasions.
Once I get a significant ANOVA, I first run a paired samples t-test using
the code:

t.test(X1,X2,paired=TRUE) #being x1 the punctuation after treatment 1 and
x2 the punctuation after
treatment 2.

After this, I run a Tukey posthoc test for repeated measures as stated in
gribblelab:

require(nlme)
a1<-lme(x~factortmnt,random=~1|factorid/factortmnt,data=mydata)
print(anova(a1))

require(multcomp)
summary(glht(a1,linfct=mcp(factortmnt="Tukey")))

The fact is that once I get both results, there are some occasions in which
I get lower p values with Tukeys correction than in paired t-tests.

How is it possible? Isn't Tukey more restrictive than paired t-tests?

Cesc

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Re: Repeated measures Tukey

Bert Gunter-2
This list is about R programming help, not statistics, although they do
sometimes overlap. However, as this appears to be entirely a statistics
issue, it really belongs on a statistics list like stats.stackexchange.com
, not here.

Cheers,
Bert



Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

On Tue, Nov 28, 2017 at 6:00 AM, Francesc Pla Juncà <[hidden email]>
wrote:

> Thanks in advance for your help.
>
> I am running a repeated measures ANOVA in r. The same group undergoes to
> four different treatment conditions. So, all individuals are treated with
> treatments A, B, C and D in four different occasions.
> Once I get a significant ANOVA, I first run a paired samples t-test using
> the code:
>
> t.test(X1,X2,paired=TRUE) #being x1 the punctuation after treatment 1 and
> x2 the punctuation after
> treatment 2.
>
> After this, I run a Tukey posthoc test for repeated measures as stated in
> gribblelab:
>
> require(nlme)
> a1<-lme(x~factortmnt,random=~1|factorid/factortmnt,data=mydata)
> print(anova(a1))
>
> require(multcomp)
> summary(glht(a1,linfct=mcp(factortmnt="Tukey")))
>
> The fact is that once I get both results, there are some occasions in which
> I get lower p values with Tukeys correction than in paired t-tests.
>
> How is it possible? Isn't Tukey more restrictive than paired t-tests?
>
> Cesc
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> 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.
>

        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
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.